Impact of digital economy development on carbon productivity:An empirical analysis based on threshold effect and spatial spillover effect

Utilizing provincial panel data from 2014 to 2020,this study employs a fixed effect model,a threshold effect model,and a spatial lag model to empirically examine the correlation between digital economic development and carbon productivity.The findings indicate that digital economic development significantly contributes to the enhancement of carbon productivity in the long term.Furthermore,through instrumental variable method,replacement of explanatory variables and other methods to test its endogeneity and stability,the results remain robust.In terms of regional heterogeneity,the impact of digital economic development on carbon productivity is less pronounced in the central and western regions compared to the eastern region.Additionally,further investigation reveals that industrial structure upgrading and science and technology investment level exhibit different threshold effects on the influence of digital economy development level on carbon productivity.Moreover,there is a significant spatial spillover effect of digital economy development on carbon productivity with H-H and L-L agglomeration spatial correlation.

Spatial spillover effects of transport infrastructure on regional economic growth

Spatial spillover effects,either positive or negative,of transport infrastructure,highways/expressways,etc.,on regional economic growth are proposed.Using the panel data for 11 cities of Zhejiang province from 1994 to 2003,a spatial production function is applied to examine the spatial spillovers which can be generated as a positive output spillover from the transport infrastructure between neighboring cities.Some spatial weighted matrices are adopted to define different neighboring cities to measure how easily factors or economic activities can migrate between regions.The estimation results show that the output elasticity of the highway infrastructure in 11 cities are all insignificant at a 5% significance level;hence,highway infrastructure in a region cannot explain the same region's economic growth.On the other hand,the highway infrastructure of other contiguous regions has positive spillover effects on a same region's economic growth.

Spatial Spillover and the Factors Influencing Public Service Supply in Sichuan Province, China

This article examines the spatial characteristics of public service supply and the factors influencing such supply in cities of Sichuan Province, China using spatial-autocorrelation and spatial econometric models with statistical data in 2012. The results demonstrate that expenditures on different types of public services present different spatial autocorrelation patterns. Although the spatial differences in basic public service expenditures are relatively small, a clear fan-shaped spillover to the east can be seen in Chengdu City. Chengdu also shows high clustering of advanced public service expenditures, being a typical core-periphery pattern. Post-earthquake reconstruction expenditures are clustered in the "5.12 Wenchuan earthquake" region and spill over toward cities to the east. The efficiency of public services in the mountainous areas in western Sichuan is low and exhibits a pattern of low-low spatial autocorrelation. The efficiency of public service supply is affected by economic, social, political and geographical factors. Based on the results of this analysis, we recommend a supply strategy that incorporates different types of public services and a specialized public service supply strategy for mountainous areas. Overall public service efficiency should be enhanced by focusing on narrowing the gap in farmers' income among regions and accelerating urbanization. Decision-makers should consider moresupportive policies with regard to providing basic public services in mountainous areas to ensure an equalized supply of basic public services. To enhance the efficiency of advanced public service supply, additional growth pole should be encouraged and incentivized; however, investments are required to drive the development of the peripheral regions through regional economic integration. Both software and hardware types of infrastructure are required to supply services efficiently during post-disaster reconstruction.

Energy consumption,air quality,and air pollution spatial spillover effects:evidence from the Yangtze River Delta of China

Based on analysis of the theoretical impact of energy consumption on air quality,taking 20 heavily polluted cities in the Yangtze River Delta of China as the object,we construct a Spatial Dubin Model,and estimate the effect of energy consumption on air quality and the spatial spillover effects of air pollution.We come to the following conclusions:First,the regional air quality has significant spatial dependence and spatial heterogeneity.Second,under three kinds of spatial associated mode,energy consumption has a negative impact on air quality,and the air pollution arising from energy consumption has a negative intra-regional spillover effect.The effect is strongest under the spatial distance weight matrix,followed by the economic distance,and the adjacent spatial weight matrix,which are−0.7926,−0.4547,and−0.4539,respectively.Third,in addition,under the adjacent space and economic distance space matrix,energy consumption has a significant negative effect on air quality,and the inter-regional spillover effects are−0.1513 and−2.5736,respectively.Meanwhile,considering spatial distance and economic development,the inter-regional spillover effect is much larger than is the intra-regional spillover effect.In general,the total spillover effect is at−0.6053 and−3.0284.

Low-carbon technology innovation responding to climate change from the perspective of spatial spillover effects

China's technological efforts to tackle climate change have lasted for many years. It is necessary to test the effect of these efforts with quantitative method. To be exact, whether and how China's low-carbon technology innovation responds to climate change should be tested. Based on the2004-2015 panel data of 30 provinces in China, we use the method of ESDA analyzing the spatial correlation of China's low-carbon innovation technology. Furthermore, we use the spatial Durbin model empirically analyzing the spatial spillover effects. The results obtained are as follows: first,supply and demand of Chinese low-carbon innovation has some deviation in the spatial distribution. The low-carbon technology innovation as the supply factor shows the characteristics of expanding from the east to the west. Innovation in eastern China has always been the most active, but innovative activities in the middle and western China are gradually decreased.However, carbon emissions have the characteristics of moving westward, implying the change of technology demand different from technology supply. Second, China's low-carbon innovation actively responds to the trend of climate change, indicating China's technological efforts have paid off. However, the spatial spillover effects are not significant, showing that the efforts in each region of China still work for himself. Third, environmental regulation and market pull are important factors for low-carbon technology innovation. Among them, both supporting policy and inhibitory policy have significant impact on the local low-carbon technology innovation, but no significant spatial spillover effects. It shows that environmental policies in different regions are competitive and lack of demonstration effects. Economic growth and export as market pull have higher level of effect on low-carbon technology innovation for both local and adjacent areas.Some policy implications are proposed based on these results finally.

The Spatial Spillover Effect of Input and Output of Scientific Progress on Regional Economic Growth: The Case of Guangdong Province

This paper makes an empirical analysis of the spatial spillover effect of regional economic growth by using Moran’s I and Spatial Durbin Model to study the input and output of technological progress, with the panel data of 21 prefecture-level cities in Guangdong Province from 2008 to 2017. The empirical results show that the spatial autocorrelation exists in the economic development of Guangdong Province, and both the input and output of scientific research innovation have a significant positive effect on the regional economic growth. Under the spatial contiguity weights matrix, the output of scientific research and innovation has a more obvious spillover effect on the economic growth of neighboring cities than the input of scientific research and innovation.

Has Transport Infrastructure Promoted Regional Economic Growth?——With an Analysis of the Spatial Spillover Effects of Transport Infrastructure

Taking full account of the synergistic effects of multidimensional factors on regional economic growth in China, this paper constructs a model of the spatial spillover effects of transport infrastructure on regional economic growth. Using provincial panel data from 1993 to 2009 and employing spatial econometric techniques, our empirical analysis comes to the following conclusions. （1） The total output elasticity of transport infrastructure for regional economic growth varies between 0.05 and 0.07, indicating its important role in such growth. （2） Transport infrastructure has very clear spatial spillover effects on regional economic growth; its role in regional economic growth will be overestimated if these are neglected. （3） For a specific region, transport infrastructure in other regions has mainly positive spillover effects on economic growth, but there is also evidence of negative spillover effects. （4） Among multidimensional factors contributing to regional economic growth, labor pluscapital stock from other parts of the public sector make the greatest contribution to regional economic growth in China, followed by the new economic growth factors and new economic geography.

Assessment of Urban Air Pollution and Spatial Spillover Effects in China: Cases of 113 Key Environmental Protection Cities

With rapid urbanization and energy consumption, environmental pollution and degradation have become increasingly serious problems in China. At the beginning of 2013, China implemented new ambient air quality standards（GB 3095-2012） in which the concentration of six pollutants including PM2.5, ozone, carbon monoxide, PM10, sulfur dioxide and nitrogen dioxide were monitored. This study gathered annual air pollutant concentration data for the six pollutants in 113 key environmental protection cites throughout China in 2014 and 2015 to explain spatial patterns of urban air pollution. Based on the Kernel density estimation method, spatial hotspots of air pollution were illustrated through which spatial cluster of each pollutants could be plotted. By employing an entropy evaluation system, urban air quality was assessed in terms of the six atmospheric pollutants. We conclude that, in general, CO and SO2 were two important pollutants in most Chinese cities, but this varied greatly among cities. The assessment results indicate that cities with the worst air quality were mainly located in northern and central provinces, dominantly in the Beijing-Tianjin-Hebei metropolitan area. Regression modeling showed that a combination of meteorological factors and human-related determinants, to say specifically, industrialization and urbanization factors, greatly influenced urban air quality variation in China. Results from spatial lag regression modeling confirmed that air pollution existed obvious spatial spillover effects among key cities. The spatial interdependence effects of urban air quality means that Chinese municipal governments should strengthen regional cooperation and deepen bilateral collaboration in terms of air regulation and pollution prevention.

Spatial Spillovers from Foreign Direct Investment： Evidence from the Yangtze River Delta in China

This paper examines the spatial externality from foreign direct investment on domestic firms. Using Chinese firm-level data for 2004, and after accounting for an endogeneity problem, we find that foreign firms generate a significantly positive spillover effect on the regional productivity of domestic firms in similar counties and industries. Estimating a spatial-autoregressive model, we further show that such local spillovers could transmit to domestic firms in other counties and industries through interactions among domestic firms. However, these spatial multiplier effects decline with distance, thereby reducing the foreign direct investment spillover effects for domestic firms in distant locations.

Regional Correlation and Spatial Spillovers in China's Regional Economic Growth

Using an exploratory spatial data analytical tool, this paper examines the spatial distribution patterns and features of GDP per capita in each of China＇s provinces. The results indicate that a positive global spatial autocorrelation exists and increases over time. At the same time, local correlation shows that China＇s local spatial agglomeration is becoming ever more marked. Based on a new economic geography model signaling the effects of market potential on regional economic development, this paper further investigates spatial spillover effects on Chinese regional economic growth through econometric analysis. Our empirical analysis shows that spatial spillovers play an important role in China＇s regional economic development. Every 1 percent increase in market potential leads to an increase of 0.47 percent in regional GDP per capita, outperforming increases in regional fixed assets investment in terms of elasticity. Of course, our analysis also shows that spatial spillover effects decrease as inter-regional distance increases.

Air pollution effects of industrial transformation in the Yangtze River Delta from the perspective of spatial spillover

The Yangtze River Delta(YRD) is a region in China with a serious contradiction between economic growth and environmental pollution. Exploring the spatiotemporal effects and influencing factors of air pollution in the region is highly important for formulating policies to promote the high-quality development of urban industries. This study uses the spatial Durbin model(SDM) to analyze the local direct and spatial spillover effects of industrial transformation on air pollution and quantifies the contribution of each factor. From 2008 to 2018, there was a significant spatial agglomeration of industrial sulfur dioxide emissions(ISDE) in the YRD, and every 1% increase in ISDE led to a synchronous increase of 0.603% in the ISDE in adjacent cities. The industrial scale index(ISCI) and industrial structure index(ISTI), as the core factors of industrial transformation, significantly affect the emissions of sulfur dioxide in the YRD, and the elastic coefficients are 0.677 and-0.368, respectively. The order of the direct effect of the explanatory variables on local ISDE is ISCI>ISTI>foreign direct investment(FDI)>enterprise technological innovation(ETI)>environmental regulation(ER)> per capita GDP(PGDP). Similarly, the order of the spatial spillover effect of all variables on ISDE in adjacent cities is ISCI>PGDP>FDI>ETI>ISTI>ER, and the coefficients of the ISCI and ISTI are 1.531 and 0.113, respectively. This study contributes to the existing research that verifies the environmental Kuznets curve in the YRD, denies the pollution heaven hypothesis, indicates the Porter hypothesis, and provides empirical evidence for the formation mechanism of regional environmental pollution from a spatial spillover perspective.

Spatial Spillovers and the Convergence of Regional Economic Growth: A Case Study Based on the Yangtze River Delta

Spatial club convergence means that the economic growth of a group of regions that have similar initial conditions and structural characteristics and are spatially adjacent will gradually converge on the same steady state. As a new field in research on the club convergence of regional economic growth, spatial club convergence works on a mechanism whereby spatial spillovers drive the localized growth of the regional economy, leading to spatial club convergence. Using a theoretical model of regional economic growth that includes spatial spillovers, this study shows that these spillovers can lead to spatial club convergence. Our empirical analysis of regional economic growth in the Yangtze River Delta in 1990-2007 also shows that spatial spillovers can affect regional economic growth, and that spatial club convergence does exist. When the spatial spillover factor is taken into account, the speed of spatial club convergence in the Yangtze River Delta is 1.57 percent.

Regional inequality, spatial spillover effects, and the factors influencing city-level energy-related carbon emissions in China

Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.

The Spatial Spillover Effects of Infrastructure on Economic Growth in Shenyang Economic Zone

This article analyses the spatial spillover effects of infrastructure on regional economic growth by using the panel data of eight cities of Shenyang Economic Zone from2001 to 2013. The empirical results of this paper indicate:(1) The infrastructure of adjacent regions have positive effects on local economic growth, demonstrating that the spillover effects of infrastructure in Shenyang Economic Zone are positive;(2) if one ignores the spillover effects of infrastructure, one will overestimate the effects of local infrastructure on local economic growth;(3) the effects of local infrastructure on local economic growth are far greater than those of adjacent regions;(4) there is great difference in spillover effects of infrastructure of different cities in the economic zone, which is related to the level of economic development.

Direct impacts and spatial spillovers:How does the multilateral resistance affect China-Africa agricultural trade?

The changes of one region’s trade barriers will affect other regions’trade volume.These spatial correlations caused by explanatory variables also constitute another part of“the multilateral resistance”,which tend to be ignored in traditional gravity equations.This paper takes this inconsistency between theoretical basis and empirical analysis as the breakthrough point of research.A multilateral gravity model is built,which has the feature of generalized spatial correlation.Then,frontier techniques of spatial econometrics are used to construct an empirical equation,and to conduct an empirical analysis,which scientifically estimate the magnitudes of bilateral direct impacts and the magnitudes of spatial spillovers on multilateral neighbors.The decomposition of the effects that provides reference for the directional operations of trade policy shows as follows:The negative factors that have significant spatial spillover effects would bring about multilateral resistance on China-Africa agricultural trade,which are caused by relatively poor social and economic conditions,corruption,and ethnic conflicts in some African countries.Energy production may cause crowding-out effects on agriculture of neighboring regions.In addition,the conflicts between African countries would hinder the development of agricultural trade between China and African countries not only because they have negative direct impacts on China-African agricultural trade but also because they have significant spatial spillover effects.When China promotes China-Africa agricultural trade by means of investment or aid,China should pay close attention to some direct or indirect impacts on the stable development of the China-African agricultural trade,which are caused by factors such as the developments of non-agricultural industries,peace,cultural consensus and efficient government.

Spatial Spillover Effects of the Impact of Agricultural Mechanization on Carbon Emission Intensity in Agriculture:An Empirical Study Based on the Panel Data of 282 Cities

The extreme weather caused by the global warming effect has triggered huge losses to agricultural production.A hot issue for governments and scholars is how to effectively reduce carbon emission intensity in agriculture.The agricultural farming practices that are high pollution and high energy cosuming have exacerbated the vulnerability of regional agroecosystems.The sustainable development of agriculture is faced with the two dilemmas of a low utilization rate of green resources and the serious pollution of farmland.Further,environmental and ecological carrying capacities have reached theirlimits,seriouslyhinderingtthe high-quality development of low-carbon agriculture in China.Thus,based on the panel data of 282 cities,the Spatial Dubin Model(SDM)is employed to examine the impact of agricultural mechanization on carbon emission intensity in agriculture.It is found that from 1999 to 2019 carbon emission intensity in agriculture showed an overall downward trend;as of 2019,the agricultural field had completed the target of carbon emission reduction,,oneyear aheadof schedule.From a local perspective,approximately 14.89%6of fagricultural industries in prefecture-level city have still not achieved carbon emission reduction targets,and agricultural carbon emission reduction tasks were better completed in major grain-producing areas than in nonmajor grain-producing areas.Agricultural mechanization has significantly reduced carbonemission intensityyinlocal agriculture production.The impact of agricultural mechanizationoncarbon emission intensity in agriculture has not only a significant negative spatial spillover effect but also a significant effect on spatial carbon emission reduction.Compared with non-major ggrain-producingareas,agricultural mechanization plays a greater role in reducing spatial carbon emissions in major grain-producing areas.Further studies find that agricultural mechanization is conducive to overcome difficulties,such as instability of property rights and land fragmentation,and to achieve large-scale agricultural production,thereby reducing agricultural carbon emissions in nearby regions.However,the transfer of rurallabor,adjustments to the structure of agricultural cultivation,and the centralized use of rural land restrict the development of the crossregional service market for agricultural machinery,which in turn weaken its contribution to spatial carbon emission reduction.At the end of this paper,it is suggested that Chinese governments at all levels should introduce subsidy policies for the cross-regional operation of agricultural machinery to solve the problem of their service market failure.Efforts should be made to stimulate the market to develop more energy-efficient and environmentally friendly agricultural machinery products while strictly controlling changes in the use of arableland in non-grain-producing areas,which aims to serve further agricultural mechanization and boost the high-quality development of low-carbon agriculture.

A Spatial Econometric Approach to Studying Regional Air Pollution in China

Using spatial econometric method,this paper investigates the mutual influence of air pollution among 31 Chinese provincial regions,together with the effects of energy mix and economic variations.Global spatial autocorrelation analysis reveals that significant positive spatial correlation exists for air pollution;Local spatial autocorrelation analysis indicates that pollution aggregation hot spots are concentrated in Beijing-Tianjin-Hebei region,the Yangtze River Delta and part of the central region between these two economic growth poles.This paper believes that industrial relocation is a major reason behind such distribution of air pollution in China as it has deepened the spatial correlation between interregional economy and pollution,which will further give rise to the spatial spillover effect of pollution.With the creation of the regression model of spatial and Environmental Kuznets Curve,the authors discovered that the level of pollution is closely related to energy mix and industrial structure.In addition,the inverted U-shape relationship between air pollution and economic development as demonstrated by previous studies does not exist or is yet to appear in China,where continuous growth of per capita GDP is accompanied by an increasing level of pollution.According to empirical analysis,the improvement of environmental quality at the expense of industrial relocation to neighboring regions is temporary.Due to the existence of spillover effect of pollution,regions that have enforced tighter environmental regulation such as Beijing and Tianjin are unable to acquire all benefits from such regulation.Treatment of air pollution necessitates interregional joint prevention and control.In the long run,adjusting energy mix and optimizing industrial structure are the key to fighting air pollution.But in the short run,reducing the consumption of inferior coal is the most effective option for China,which has seen multiple-fold increase in imports of inferior coal each year.

The effects of PM_(2.5)concentration on residents'health from the perspective of spatial economics

Ambient air quality is an important part of the ecological environment.Based on panel data from 192 countries for the period 2010–2016,our study applies spatial geography elements in a spatial panel model to analyze whether PM_(2.5)harms residents'health.We find a positive correlation between PM_(2.5)concentration and the prevalence of tuberculosis.Empirical testing shows that if residents live in environments with high PM_(2.5)concentrations for an extended period,it increases their probability of contracting tuberculosis.PM_(2.5)concentration and economic growth have an environmental Kuznets curve(EKC)relationship.Furthermore,PM_(2.5)concentration and prevalence of tuberculosis in different countries have a positive spatial correlation during the study period.The values of PM_(2.5)concentration in adjacent areas are similar,because PM_(2.5)can cross borders through airflow and as economic development levels in adjacent regions are similar.When regulating haze pollution,we should adopt regional joint governance,consider the specific characteristics of different regions,and coordinate these regulations with environmental protection policies to realize the goal of“lucid waters and lush mountains.”

Evolution and Determinants of Population Agglomeration in Less Developed Metropolitan Areas:A Case Study of the Taiyuan Metropolitan Area,China

It is of importance to enhance the urban areas'capacity for population aggregation in underdeveloped regions,aiming to rectify the imbalanced and insufficient pattern of economic development in China.Taking the Taiyuan Metropolitan Area(TMA)in central China as a case study,this paper examines the evolutionary process and characteristics of population agglomeration from 2000 to 2020,and identifies factors associated with agglomeration and their spatial effects.The findings indicated that:1)against the background of sustained population shrinkage in the provincial area,the TMA showed a demographic trend of steady increase,albeit with a decelerated growth rate.In the metropolitan area,urban population size continued to grow rapidly,whereas the rural areas endured sustained losses.Disparities in city size continued to widen,and the polarization of concentrated population in the core cities kept increasing.2)Agglomerations in both secondary and service industries had significant positive effects on local population agglomeration,with the former effect being stronger.Regional economic development,government fiscal expenditure,and financial advancement all contributed to facilitating local population clustering.From a spatial spillover perspective,service agglomeration and financial development promoted population agglomeration in surrounding areas.Conversely,fiscal expenditure inhibited such agglomeration.As for industrial agglomeration and regional economic development,their spatial spillover effects were non-significant.The results obtained reveal several policy implications aimed at enhancing the population agglomeration capacity of the metropolitan area in underdeveloped regions during the new era.

Synergistic dance of digital economy and green finance on carbon emissions:Insights from China

China has recently implemented a dual-carbon strategy to combat climate change and other environmental issues and is committed to modernizing it sustainably.This paper supports these goals and explores how the digital economy and green finance intersect and impact carbon emissions.Using panel data from 30 Chinese provinces over the period 2011-2021,this paper finds that the digital economy and green finance can together reduce carbon emissions,and conducts several robustness tests supporting this conclusion.A heterogeneity analysis shows that these synergistic effects are more important in regions with low levels of social consumption Meanwhile,in the spatial dimension,the synergistic effect of the local digital economy and green finance adversely impacts the level of carbon emissions in surrounding areas.The findings of this paper provide insights for policymakers in guiding capital flow and implementing carbon-reduction policies while fostering the growth of China’s digital economy and environmental sustainability.