The rural fundamental and productive fixed-asset investment not only makes active influence on the changes of farmers' operational,wages and property income,but it also has an optimal scale range for farmers' ...The rural fundamental and productive fixed-asset investment not only makes active influence on the changes of farmers' operational,wages and property income,but it also has an optimal scale range for farmers' income increase. From the perspective of farmers' income increase,this article evaluates the optimal scale of rural fixed-asset investment by setting up model with statistic data,and the results show that the optimal scale of per capita rural fixed-asset investment is 76. 35% of per capita net income of rural residents,which has been reached in China in 2009. Therefore,compared with the adding of rural fixed-asset investment,a better income increase effect can be achieved through the adjustment of rural fixed-asset investment structure.展开更多
Under China’s“Dual Carbon”target(DCT),“clean replacement”on the energy supply side and“electric energy replacement”on the energy consumption side are the ways to achieve energy transformation.However,energy pro...Under China’s“Dual Carbon”target(DCT),“clean replacement”on the energy supply side and“electric energy replacement”on the energy consumption side are the ways to achieve energy transformation.However,energy projects have a long construction period,complex technology categories,and investment risks that greatly affect the development of energy transformation.Correctly judging the effect of investment changes on primary energy production is of great practical significance to the realization of the DCT.Based on this,NARDL and TVP-SV-VAR models are innovatively used to reveal the nonlinear effect of fixed-asset investment on China’s primary energy production.The results show that the marginal effect of investment growth on coal production is about 1.44 times that of investment reduction.Similarly,the marginal effect of oil and gas investment growth is about 1.21times that of investment reduction.Due to the influence of resource constraints,China’s traditional fossil energy still has varying degrees of path dependence on the investment-driven development model.For non-fossil energy,investment in hydropower and nuclear power has an inverse correlation with the change in production.Negative marginal efficiency and diseconomies of scale have hindered the development of the hydropower and nuclear power industries.In addition,the asymmetric effect is not yet significant for the short development time and technical constraints of wind and solar power.From the impulse response results,the impact curves of investment in wind and solar power are generally positive,and investment has different degrees of time-delay and time-varying effects on various energy production,which verifies the heterogeneity of investment adjustment mechanisms in different energy industries.展开更多
Low carbon productivity has been identified as a key direction for China’s future development.As an important driving force for economic growth,the question of whether digital finance that is reliant on digital techn...Low carbon productivity has been identified as a key direction for China’s future development.As an important driving force for economic growth,the question of whether digital finance that is reliant on digital technology can support the development of a low-carbon urban economy remains unresolved.Based on the carbon productivity measured by panel data from 201 cities for the period 2011-2020,this study applies the spatial Dubin model and threshold regression model to explore the impact of digital finance on carbon productivity,yielding the following key conclusions.First,the spatial distribution heterogeneity of carbon productivity in China’s eastern region is higher than that in the western region,and both productivity and digital finance are characterized by high(low)-high(low)dotted spatial agglomeration.Second,digital finance can significantly improve carbon productivity via two transmission channels:the human capital and marketization effects.At the same time,digital finance exerts a spatial spillover effect on carbon productivity,and rising local digital finance levels will increase carbon productivity in neighboring areas.Heterogeneity analysis indicates that the spillover effect of digital finance in urban agglomerations and eastern regions is more significant.Third,fixed-asset investment has a positive nonlinear moderating effect on digital finance,thus improving carbon productivity.When the per capita investment in fixed assets does not exceed 682.73 yuan,digital finance exerts only a limit pulling effect on carbon productivity;when it is higher than this value,the pulling effect is intensified.展开更多
From Jan.to Aug.2009,total statistics-worthy fixed-assets investment (over CNY 5million) in the textile industry was up 6.55% to CNY 188.245 billion year-on-year,but that was 4.58 percentage points less than the growt...From Jan.to Aug.2009,total statistics-worthy fixed-assets investment (over CNY 5million) in the textile industry was up 6.55% to CNY 188.245 billion year-on-year,but that was 4.58 percentage points less than the growth rate of the same period last year.During the Jan.-Aug.展开更多
Fixed asset investment growth in China’s textile industry slowed in the first three quarters this year, mainly resulting from the yuan appreciation, the rising material and labor costs, as well as dismal overseas mar...Fixed asset investment growth in China’s textile industry slowed in the first three quarters this year, mainly resulting from the yuan appreciation, the rising material and labor costs, as well as dismal overseas market hit by the subprime lending crisis. From January to September, the total fixed-assets investment in the textile industry was up 10.15% to RMB 202.269 billion year-on-year,展开更多
基金Supported by the Fundamental Research Funds for the Central Universities(SWU1409308)
文摘The rural fundamental and productive fixed-asset investment not only makes active influence on the changes of farmers' operational,wages and property income,but it also has an optimal scale range for farmers' income increase. From the perspective of farmers' income increase,this article evaluates the optimal scale of rural fixed-asset investment by setting up model with statistic data,and the results show that the optimal scale of per capita rural fixed-asset investment is 76. 35% of per capita net income of rural residents,which has been reached in China in 2009. Therefore,compared with the adding of rural fixed-asset investment,a better income increase effect can be achieved through the adjustment of rural fixed-asset investment structure.
基金supported by the National Natural Science Foundation of China under Grant No.71874133the Youth Innovation Team of Shaanxi Universities under Grant No.2020-68+1 种基金Shaanxi Province Qin Chuangyuan“Scientist+Engineer”Team Building Project under Grant No.2022KXJ-007the Seed Foundation of Innovation Practice for Graduate Students in Xidian University under Grant No.2021-26。
文摘Under China’s“Dual Carbon”target(DCT),“clean replacement”on the energy supply side and“electric energy replacement”on the energy consumption side are the ways to achieve energy transformation.However,energy projects have a long construction period,complex technology categories,and investment risks that greatly affect the development of energy transformation.Correctly judging the effect of investment changes on primary energy production is of great practical significance to the realization of the DCT.Based on this,NARDL and TVP-SV-VAR models are innovatively used to reveal the nonlinear effect of fixed-asset investment on China’s primary energy production.The results show that the marginal effect of investment growth on coal production is about 1.44 times that of investment reduction.Similarly,the marginal effect of oil and gas investment growth is about 1.21times that of investment reduction.Due to the influence of resource constraints,China’s traditional fossil energy still has varying degrees of path dependence on the investment-driven development model.For non-fossil energy,investment in hydropower and nuclear power has an inverse correlation with the change in production.Negative marginal efficiency and diseconomies of scale have hindered the development of the hydropower and nuclear power industries.In addition,the asymmetric effect is not yet significant for the short development time and technical constraints of wind and solar power.From the impulse response results,the impact curves of investment in wind and solar power are generally positive,and investment has different degrees of time-delay and time-varying effects on various energy production,which verifies the heterogeneity of investment adjustment mechanisms in different energy industries.
基金supported by the National Natural Science Foundation of China(72243005)the National Social Science Fund of China(21AZD067)the Key Program of Collaborative Innovation Center for Emissions Trading system Co-constructed by the Province and Ministry in Hubei University of Economics(22CICETS-ZD005).
文摘Low carbon productivity has been identified as a key direction for China’s future development.As an important driving force for economic growth,the question of whether digital finance that is reliant on digital technology can support the development of a low-carbon urban economy remains unresolved.Based on the carbon productivity measured by panel data from 201 cities for the period 2011-2020,this study applies the spatial Dubin model and threshold regression model to explore the impact of digital finance on carbon productivity,yielding the following key conclusions.First,the spatial distribution heterogeneity of carbon productivity in China’s eastern region is higher than that in the western region,and both productivity and digital finance are characterized by high(low)-high(low)dotted spatial agglomeration.Second,digital finance can significantly improve carbon productivity via two transmission channels:the human capital and marketization effects.At the same time,digital finance exerts a spatial spillover effect on carbon productivity,and rising local digital finance levels will increase carbon productivity in neighboring areas.Heterogeneity analysis indicates that the spillover effect of digital finance in urban agglomerations and eastern regions is more significant.Third,fixed-asset investment has a positive nonlinear moderating effect on digital finance,thus improving carbon productivity.When the per capita investment in fixed assets does not exceed 682.73 yuan,digital finance exerts only a limit pulling effect on carbon productivity;when it is higher than this value,the pulling effect is intensified.
文摘From Jan.to Aug.2009,total statistics-worthy fixed-assets investment (over CNY 5million) in the textile industry was up 6.55% to CNY 188.245 billion year-on-year,but that was 4.58 percentage points less than the growth rate of the same period last year.During the Jan.-Aug.
文摘Fixed asset investment growth in China’s textile industry slowed in the first three quarters this year, mainly resulting from the yuan appreciation, the rising material and labor costs, as well as dismal overseas market hit by the subprime lending crisis. From January to September, the total fixed-assets investment in the textile industry was up 10.15% to RMB 202.269 billion year-on-year,
