scholarly journals The effect of total factor productivity of forestry industry on CO2 emissions: a spatial econometric analysis of China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shen Zhong ◽  
Hongli Wang
Keyword(s):  
Total Factor Productivity ◽  
Industrial Structure ◽  
Spillover Effect ◽  
Factor Productivity ◽  
Spatial Econometric ◽  
Spatial Spillover ◽  
Negative Case ◽  
Forestry Industry ◽  
The Impact ◽  
Spatial Spillover Effect

AbstractForestry plays an essential role in reducing CO2 emissions and promoting green and sustainable development. This paper estimates the CO2 emissions of 30 provinces in China from 2008 to 2017, and uses Global DEA-Malmquist to measure the total factor productivity of the forestry industry and its decomposition index. On this basis, by constructing a spatial econometric model, this paper aims to empirically study the impact of forestry industry's total factor productivity and its decomposition index on CO2 emissions, and further analyze its direct, indirect and total effects. The study finds that the impact of forestry industry's total factor productivity on CO2 emissions shows an "inverted U-shaped" curve and the inflection point is 0.9395. The spatial spillover effect of CO2 emissions is significantly negative. The increase of CO2 emissions in adjacent areas will provide a "negative case" for the region, so that the region can better address its own energy conservation and emission reduction goals. TFP of forestry industry also has positive spatial spillover effect. However, considering the particularity of forestry industry, this effect is not very significant. For other factors, such as foreign direct investment, urbanization level, industrial structure and technology market turnover will also significantly affect regional CO2 emissions.

Research on the Spatial Effect of Green Economic Efficiency in China from the Perspective of Informatization

2020 ◽  
Author(s):  
Xinbao Tian ◽  
Chuanhao Yu
Keyword(s):  
Industrial Structure ◽  
Spillover Effect ◽  
Coordination Mechanism ◽  
Green Economy ◽  
Spatial Econometric ◽  
Index Method ◽  
Spatial Spillover ◽  
Regional Coordination ◽  
Comprehensive Index Method ◽  
Spatial Spillover Effect

Abstract Background: Green economy has been paid more and more attention in the information age. Informatization plays an important role in the development of green economy by the transmission of industrial structure rationalization and upgrading. Because of the spatial mobility of information, it is necessary to study the spatial spillover effect of information on the efficiency of green economy. In this paper, the non-radial directional distance function and the comprehensive index method are used to evaluate the efficiency of green economy and informatization respectively. On this basis, the spatial characteristics of the two are analyzed. Finally, the spatial econometric model is used to analyze the spatial impact of informatization on the efficiency of green economy. Results: The following findings can be drawn: (i)The spatial distribution of the green economy efficiency and informatization are unbalanced; (ii) There is a significant spatial spillover effect in the efficiency of green economy; (iii) The development of informatization plays an important impact on the efficiency of green economy. Conclusions: It can be seen that informatization plays an important role in the development of green economy, so we can get the following suggestions: (i) Developing green economy according to different conditions of different places. (ii) Establishing regional coordination mechanism of green economic development. (iii) Using informatization to promote the development of green economy.

scholarly journals Environmental Regulation, Resource Misallocation and Industrial Total Factor Productivity: A Spatial Empirical Study Based on China’s Provincial Panel Data

2021 ◽  
Vol 13 (4) ◽  
pp. 2390
Author(s):  
Xu Dong ◽  
Yali Yang ◽  
Xiaomeng Zhao ◽  
Yingjie Feng ◽  
Chenguang Liu
Keyword(s):  
Panel Data ◽  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Spillover Effect ◽  
Factor Productivity ◽  
Resource Reallocation ◽  
Spatial Spillover ◽  
Resource Misallocation ◽  
Capital Misallocation ◽  
Spatial Spillover Effect

A vast theoretical and empirical literature has been devoted to exploring the relationship between environmental regulation and total factor productivity (TFP), but no consensus has been reached and the reason may be attributed to the fact that the resource reallocation effect of environmental regulation is ignored. In this paper, we introduce resource misallocation in the process of discussing the impact of environmental regulation on TFP, taking China’s provincial industrial panel data from 1997 to 2017 as a sample, and the spatial econometric method is employed to investigate whether environmental regulation has a resource reallocation effect and affects TFP. The results indicate that there is a U-shaped relationship between environmental regulation and industrial TFP and a negative spatial spillover effect of environmental regulation on industrial TFP at the provincial level in China. Both capital misallocation and labor misallocation will lead to the loss of industrial TFP. Capital misallocation has a negative spatial spillover effect on industrial TFP, while labor misallocation is just the opposite. Environmental regulation can produce a positive resource reallocation effect, which in turn promotes the industrial TFP in the range of 28% to 33%, while capital misallocation and labor misallocation are only partial mediator.

scholarly journals Temporal-Spatial Evolution and Driving Factors of the Green Total Factor Productivity of China’s Central Plains Urban Agglomeration

2021 ◽  
Vol 9 ◽  
Author(s):  
Fengting Wang ◽  
Ruichao Li ◽  
Chang Yu ◽  
Lichun Xiong ◽  
Yuan Chang
Keyword(s):  
Total Factor Productivity ◽  
Industrial Structure ◽  
Spillover Effect ◽  
Measurement Model ◽  
Urban Agglomeration ◽  
Factor Productivity ◽  
Spatial Econometric ◽  
Central Plains ◽  
Productivity Level ◽  
Factors Affecting

As China’s largest urban agglomeration with rapid growth of economy and population, the development of the Central Plains Urban Agglomeration (CPUA) has been severely restricted by environmental problems. Thus, the green development performance of the CPUA is worth studying. This study used the panel data of 29 cities in the CPUA from 2003 to 2018 based on the Slacks-based Measure and Global Malmquist–Luenberger index to measure the green total factor productivity (GTFP) and its decomposition index of each city. A spatial econometric model was developed to explore the factors affecting the GTFP of the CPUA. The results show that the GTFP of the CPUA had an upward trend in 2003–2018, but the productivity level was still low. There were significant spillover effect in the GTFP among different cities of the CPUA. The results of the spatial measurement model show that technological progress, industrial structure and solid waste environmental regulationhave a significant positive spillover effect on the GTFP. The, fiscal expenditure, and informatization level also have positive impacts on the GTFP. In the future, local government should provide technical and financial support for the development of green industries in the CPUA, and accelerate the construction of environmental protection infrastructures.

scholarly journals Reexamining the Impact of Industrial Structure on Haze Pollution Based on the Yangtze River Delta

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 613
Author(s):  
Lu Wang ◽  
Shumin Jiang ◽  
Hua Xu
Keyword(s):  
Yangtze River ◽  
Industrial Structure ◽  
Spillover Effect ◽  
Inhibitory Effect ◽  
Yangtze River Delta ◽  
River Delta ◽  
Spatial Spillover ◽  
Haze Pollution ◽  
The Impact ◽  
Spatial Spillover Effect

In this study, the static and dynamic spatial Durbin model between industrial structure and haze pollution in Yangtze River Delta is constructed. Later, the spatial spillover effect and time lag effect of haze pollution in Yangtze River Delta are analyzed. The impact of rationalization and upgrading of industrial structure on haze pollution and its spatial spillover effect are discussed. The results show that: (i) PM2.5 has a significant positive spatial spillover effect and time lag effect; (ii) in the short run, the rationalization and upgrading of industrial structure has no inhibitory effect on haze pollution, while the rationalization and upgrading of industrial structure of surrounding cities has an inhibitory effect on local haze pollution; (iii) in the long run, the rationalization and upgrading of industrial structure of surrounding cities have an inhibitory effect on local haze pollution; (iv) economic growth, FDI, the number of Industrial Enterprises above Designated Size, and population density also have spatial spillover effects on haze pollution. Therefore, considering the spatial spillover effect of haze pollution from the perspective of urban agglomeration and long-term, strengthening the joint prevention and control and comprehensive treatment among cities, further promoting the rationalization and upgrading of industrial structure is conducive to reducing haze pollution.

scholarly journals Impact of Financial Development and Its Spatial Spillover Effect on Green Total Factor Productivity: Evidence from 30 Provinces in China

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Junhao Zhong ◽  
Tinghui Li
Keyword(s):  
Total Factor Productivity ◽  
Financial Development ◽  
Spillover Effect ◽  
Policy Implications ◽  
Pollutant Emissions ◽  
Factor Productivity ◽  
Spatial Spillover ◽  
Surrounding Areas ◽  
The Relationship ◽  
Spatial Spillover Effect

The relationship between financial development and green economic growth has received much attention in recent years. Research on the relationship between financial development and green total factor productivity (GTFP) is of great importance to China and other countries. This study has attempted to reveal the spatial distribution of China’s provincial GTFP and impact of financial development on GTFP by using the method of GML index based on SBM-DDF and the spatial Durbin model (SDM) during the period 1996–2015. Innovation is added to the SDM to reflect the influencing mechanism of financial development on GTFP. The empirical results show the following: (1) The mean of China’s provincial GTFP showed a U-shaped curve in 1996–2015. (2) China’s provincial financial development promotes the growth of GTFP through innovation channel. The reason is that financial development boosts eco-friendly innovation and the introduction of energy saving technology, leading to a decrease in energy consumption and pollutant emissions. (3) Increasing the level of financial development in the surrounding areas will restrain local GTFP. Our results provide new evidence that China’s regional financial development has a spatial spillover effect. (4) China’s provincial GTFP has a significant spatial positive correlation. Finally, several policy implications can be summarized to China’s 30 provinces.

scholarly journals Internet Development and Environmental Quality—Evidence from the Development of Chinese Cities

2021 ◽  
Vol 13 (20) ◽  
pp. 11308
Author(s):  
Xiaoying Zhong ◽  
Ruhe Xie ◽  
Peng Chen ◽  
Kaili Ke
Keyword(s):  
Environmental Quality ◽  
Industrial Structure ◽  
Spillover Effect ◽  
Mediating Effect ◽  
The Internet ◽  
Eastern Region ◽  
Spatial Spillover ◽  
Internet Development ◽  
The Impact ◽  
Spatial Spillover Effect

Based on the data of the 283 prefecture-level cities in China from 2003 to 2018, this paper examines the impact of Internet development on environmental quality. The results show that China’s urban PM2.5 has a significant spatial spillover effect. In general, the Internet has a significant negative direct effect on urban environmental pollution, which means that the development of the Internet can improve urban environmental quality. This result remains robust under different methods. As the Internet has evolved over the years, its influence on environmental quality has increased and became more and more significant. In terms of regions, the spatial spillover effect of PM2.5 shows a pattern of eastern region < central region < western region < northeast region, where the eastern region is the only region with a statistically significant negative value for the coefficient, which indicates the direct effects of Internet development on the environmental quality. In addition, the statistic testing on mediating effect shows that the Internet’s effect on urban environment quality is mainly transmitted through the upgrading of industrial structure. With the industrial structure being used as the threshold variable, the influence of Internet development on environmental quality could be divided into two stages.

scholarly journals Empirical Study of the Spatial Spillover Effect of Transportation Infrastructure on Green Total Factor Productivity

2020 ◽  
Vol 13 (1) ◽  
pp. 326
Author(s):  
Xi Liang ◽  
Pingan Li
Keyword(s):  
Total Factor Productivity ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Transportation Infrastructure ◽  
Factor Productivity ◽  
Spatial Durbin Model ◽  
Spatial Spillover ◽  
Spatial Spillover Effects ◽  
Dynamic Spatial Durbin Model ◽  
Spatial Spillover Effect

Transportation infrastructure promotes the regional flow of production. The construction and use of transportation infrastructure have a crucial effect on climate change, the sustainable development of the economy, and Green Total Factor Productivity (GTFP). Based on the panel data of 30 provinces in China from 2005 to 2017, this study empirically analyses the spatial spillover effect of transportation infrastructure on the GTFP using the Malmquist–Luenberger (ML) index and the dynamic spatial Durbin model. We found that transportation infrastructure has direct and spatial spillover effects on the growth of GTFP; highway density and railway density have significant positive spatial spillover effects, and especially-obvious immediate and lagging spatial spillover effects in the short-term. We also note that the passenger density and freight density of transportation infrastructure account for a relatively small contribution to the regional GTFP. Considering environmental pollution, energy consumption, and the enriching of the traffic infrastructure index system, we used the dynamic spatial Durbin model to study the spatial spillover effects of transportation infrastructure on GTFP.

scholarly journals Effect of Complex Road Networks on Intensive Land Use in China’s Beijing-Tianjin-Hebei Urban Agglomeration

Land ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 532
Author(s):  
Chen Zeng ◽  
Zhe Zhao ◽  
Cheng Wen ◽  
Jing Yang ◽  
Tianyu Lv
Keyword(s):  
Land Use ◽  
Road Network ◽  
Spillover Effect ◽  
Urban Agglomeration ◽  
Land Use Intensity ◽  
Spatial Econometric ◽  
Spatial Spillover ◽  
The Road ◽  
Intensive Land Use ◽  
Spatial Spillover Effect

Coupled with rapid urbanization and urban expansion, the spatial relationship between transportation development and land use has gained growing interest among researchers and policy makers. In this paper, a complex network model and land use intensity assessment were integrated into a spatial econometric model to explore the spatial spillover effect of the road network on intensive land use patterns in China’s Beijing–Tianjin–Hebei (BTH) urban agglomeration. First, population density, point of interest (POI) density, and aggregation index were selected to measure land use intensity from social, physical, and ecological aspects. Then, the indicator of average degree (i.e., connections between counties) was used to measure the characteristics of the road network. Under the hypothesis that the road network functions in shaping land use patterns, a spatial econometric model with the road network embedded spatial weight matrix was established. Our results revealed that, while the land use intensity in the BTH urban agglomeration increased from 2010 to 2015, the road network became increasingly complex with greater spatial heterogeneity. The spatial lag coefficients of land use intensity were positively significant in both years and showed a declining trend. The spatially lagged effects of sector structure, fixed asset investment, and consumption were also significant in most of our spatial econometric models, and their contributions to the total spillover effect increased from 2010 to 2015. This study contributes to the literature by providing an innovative quantitative method to analyze the spatial spillover effect of the road network on intensive land use. We suggest that the spatial spillover effect of the road network could be strengthened in the urban–rural interface areas by improving accessibility and promoting population, resource, and technology flows.

Sign in / Sign up

Export Citation Format

Share Document