Based on the threshold panel data model,this paper analyzed the nonlinear relationship between chemical fertilizer input and grain output. At the provincial level,from the perspective of average and marginal net benef...Based on the threshold panel data model,this paper analyzed the nonlinear relationship between chemical fertilizer input and grain output. At the provincial level,from the perspective of average and marginal net benefits,it compared the effects of chemical fertilizer input on farmers' income. It reached the conclusion that the chemical fertilizer input efficiency has deviated from the optimal level. Thus,only by increasing the marginal productivity of chemical fertilizers,may it be able to increase farmers' income.展开更多
Great Lakes Regions(GLRs)in China often confront landscape fragmentation,wetland degradation,and ecological resilience(ER)losses owing to extensive and intensive urbanization.In GLRs,however,the ER responses to urbani...Great Lakes Regions(GLRs)in China often confront landscape fragmentation,wetland degradation,and ecological resilience(ER)losses owing to extensive and intensive urbanization.In GLRs,however,the ER responses to urbanization remain unclear.This study explored the spatiotemporal evolution of ER and urbanization in five GLRs in China to analyze the ER dynamic patterns along center−lakeside−periphery gradient.The Spatial Durbin Model(SDM)and Panel Threshold Model(PTM)were combined to reveal the spillover and threshold effects of urbanization in five GLRs.The results indicate that the ER in five GLRs declined with a rate of 21%from 2000 to 2020.There was a clear“center-periphery”contraction trend with low ER areas primarily spreading to human activity-concentrated regions such as lakesides,riversides,and road networks.Driven by economic and land urbanization,the average urbanization level increased from 0.06 to 0.13,where lakesides,riversides,and road networks were key areas undergoing expansion.The urbanization showed a noticeable negative spatial spillover effect on ER.Away from central lakes,the negative impacts on ER exhibited a two-phase decrease with the threshold of 81 km.This study contributes to the understanding of human-environment interactions by examining the ecological resilience response process of GLRs under the impact of urbanization.Based on a multidimensional“center−lakeside−periphery”analytical model,this study provides a strategic framework for ecological construction in GLRs in China,promoting sustainable development and adaptive capacity in vulnerable areas.展开更多
Global population aging trends are intensifying,presenting multifaceted economic and social challenges for countries worldwide.As the world’s largest developing country,China has entered a phase of extreme demographi...Global population aging trends are intensifying,presenting multifaceted economic and social challenges for countries worldwide.As the world’s largest developing country,China has entered a phase of extreme demographic aging,posing significant questions about its impact on the ongoing upgrading of industrial structures.How does this demographic shift influence the upgrading of industrial structures,and does technological innovation mitigate or exacerbate this impact?The empirical results indicate that population aging impedes upgrading the industrial structure,while technological innovation positively affects the relationship between the two.Moreover,using technological innovation as a threshold variable,the impact of population aging on industrial structure upgrading evolves in a“gradient”manner from“impediment”to“insignificant”to“promotion”as the technological innovation levels increase.These findings offer practical guidance for tailoring industrial policies to different stages of technological advancement.展开更多
In the backdrop of“dual-carbon”strategic objectives,understanding the influence of the digital economy(DE)on carbon emissions(CEs)is imperative.However,there is limited research on the DE’s negative impact on CEs a...In the backdrop of“dual-carbon”strategic objectives,understanding the influence of the digital economy(DE)on carbon emissions(CEs)is imperative.However,there is limited research on the DE’s negative impact on CEs and the nonlinear relationship between the DE and CE.To address this gap,we collected data from 270 Chinese cities from 2011 to 2021 and used benchmark regression,mediated effects,and panel threshold models to explore the DE’s impact on CEs.The results showed that DE had a nonlinear,inverted U-shaped effect on CEs,with CEs initially increasing and then being suppressed.This conclusion remained consistent even after a series of robustness tests.Overall,the rate of urbanization and breadth of digital financial coverage mediate the relationship between the DE and CEs.Additionally,the combined effects of economic development,environmental regulation,fiscal decentralization,and population size contribute to the DE’s nonlinear impact on CEs.The impact of the DE on CEs varies among nonresource-based,resource-based,and resource-depleted cities and between urban and nonurban agglomerations.This paper’s findings support the development of the DE and the formulation of CE reduction policies.展开更多
Economic growth and environmental pollution have become the bases of geopolitical competition due to the multiple constraints of growth in energy consumption and environmental protection in recent decades.Whether the ...Economic growth and environmental pollution have become the bases of geopolitical competition due to the multiple constraints of growth in energy consumption and environmental protection in recent decades.Whether the coordinated development of inward foreign direct investment(IFDI)and outward foreign direct investment(OFDI)promote economic growth while reducing environmental pollution and realizing high-quality development affects the overall socialist modernization under China’s“Dual Circulation”policy.Using China’s provincial panel data from 2005 to 2020,this paper first measured green total factor productivity(GTFP)and the coordinated development index(CDIFDI)of IFDI and OFDI via the slacks-based measureglobal Malmquist–Luenberger(SBM-GML)model and the capacity coupling model.A panel threshold model with interactive effects(PTIFEs)was then applied to explore the nonlinear impact of the CDIFDI on China’s GTFP.Finally,a regional heterogeneity analysis was conducted for China’s eastern,central and western regions of China.Results show that(1)GTFP in China kept rising with small fluctuations during the sample period,with the increasing range of GTFP decreasing from east to west.(2)CDIFDI had a significant“U”-shaped threshold effect on GTFP,and the main threshold variables were the industrial structure and the level of economic development.(3)CDIFDI played a positive role in promoting GTFP growth in the eastern region,while the effects of CDIFDI on GTFP in the central and western regions were not significant.Policy-makers and enterprises should comprehensively consider promoting regional industrial upgrading and economic growth to achieve a greater positive impact of CDIFDI on GTFP.Scientifically measuring GTFP and exploring the nonlinear impact of the CDIFDI on GTFP and regional heterogeneity provide helpful references for policy-makers to coordinate the high-quality development of regional economies.展开更多
文摘Based on the threshold panel data model,this paper analyzed the nonlinear relationship between chemical fertilizer input and grain output. At the provincial level,from the perspective of average and marginal net benefits,it compared the effects of chemical fertilizer input on farmers' income. It reached the conclusion that the chemical fertilizer input efficiency has deviated from the optimal level. Thus,only by increasing the marginal productivity of chemical fertilizers,may it be able to increase farmers' income.
基金supported by the National Natural Science Foundation of China(Grants No.42301226,42271209 and 42471199)the Fundamental Research Funds for the Central Universities(Grant No.2024CDJXY014)+2 种基金the Natural Science Foundation of Jiangxi Province(Grant No.20242BAB25170)Special Funds for Water Resources in Jiangxi Province(Science and Technology Projects)(Grant No.202425YBKT16)the Young Talent Cultivation and Innovation Fund Project of Nanchang University(Grant No.XX202506030028).
文摘Great Lakes Regions(GLRs)in China often confront landscape fragmentation,wetland degradation,and ecological resilience(ER)losses owing to extensive and intensive urbanization.In GLRs,however,the ER responses to urbanization remain unclear.This study explored the spatiotemporal evolution of ER and urbanization in five GLRs in China to analyze the ER dynamic patterns along center−lakeside−periphery gradient.The Spatial Durbin Model(SDM)and Panel Threshold Model(PTM)were combined to reveal the spillover and threshold effects of urbanization in five GLRs.The results indicate that the ER in five GLRs declined with a rate of 21%from 2000 to 2020.There was a clear“center-periphery”contraction trend with low ER areas primarily spreading to human activity-concentrated regions such as lakesides,riversides,and road networks.Driven by economic and land urbanization,the average urbanization level increased from 0.06 to 0.13,where lakesides,riversides,and road networks were key areas undergoing expansion.The urbanization showed a noticeable negative spatial spillover effect on ER.Away from central lakes,the negative impacts on ER exhibited a two-phase decrease with the threshold of 81 km.This study contributes to the understanding of human-environment interactions by examining the ecological resilience response process of GLRs under the impact of urbanization.Based on a multidimensional“center−lakeside−periphery”analytical model,this study provides a strategic framework for ecological construction in GLRs in China,promoting sustainable development and adaptive capacity in vulnerable areas.
基金supported by the Research Center for Aging Career and Industrial Development,Sichuan Key Research Base of Social Sciences[Grant No.XJLL2022009].
文摘Global population aging trends are intensifying,presenting multifaceted economic and social challenges for countries worldwide.As the world’s largest developing country,China has entered a phase of extreme demographic aging,posing significant questions about its impact on the ongoing upgrading of industrial structures.How does this demographic shift influence the upgrading of industrial structures,and does technological innovation mitigate or exacerbate this impact?The empirical results indicate that population aging impedes upgrading the industrial structure,while technological innovation positively affects the relationship between the two.Moreover,using technological innovation as a threshold variable,the impact of population aging on industrial structure upgrading evolves in a“gradient”manner from“impediment”to“insignificant”to“promotion”as the technological innovation levels increase.These findings offer practical guidance for tailoring industrial policies to different stages of technological advancement.
基金supported by the National Social Science Foundation of China(Grant No.22BTJ048)the National Natural Science Foundation of China(Grant No.72403001)+4 种基金the Social Sciences Planning Youth Project of Anhui Province(Grant No.AHSKQ2022D138)the Natural Science Foundation of Anhui Province(Grant No.2408085QG228)the Anhui Province Excellent Young Talents Fund Program of Higher Education Institutions(Grant No.2023AH030015)the Innovation Development Research Project of Anhui Province(Grant No.2023CX507)the Scientific Research Project of Anhui University of Finance and Economics(Grant No.ACYC2022505).
文摘In the backdrop of“dual-carbon”strategic objectives,understanding the influence of the digital economy(DE)on carbon emissions(CEs)is imperative.However,there is limited research on the DE’s negative impact on CEs and the nonlinear relationship between the DE and CE.To address this gap,we collected data from 270 Chinese cities from 2011 to 2021 and used benchmark regression,mediated effects,and panel threshold models to explore the DE’s impact on CEs.The results showed that DE had a nonlinear,inverted U-shaped effect on CEs,with CEs initially increasing and then being suppressed.This conclusion remained consistent even after a series of robustness tests.Overall,the rate of urbanization and breadth of digital financial coverage mediate the relationship between the DE and CEs.Additionally,the combined effects of economic development,environmental regulation,fiscal decentralization,and population size contribute to the DE’s nonlinear impact on CEs.The impact of the DE on CEs varies among nonresource-based,resource-based,and resource-depleted cities and between urban and nonurban agglomerations.This paper’s findings support the development of the DE and the formulation of CE reduction policies.
基金supported by the Key Project of National Philosophy and Social Science Foundation of China(Grant No.24AGL007).
文摘Economic growth and environmental pollution have become the bases of geopolitical competition due to the multiple constraints of growth in energy consumption and environmental protection in recent decades.Whether the coordinated development of inward foreign direct investment(IFDI)and outward foreign direct investment(OFDI)promote economic growth while reducing environmental pollution and realizing high-quality development affects the overall socialist modernization under China’s“Dual Circulation”policy.Using China’s provincial panel data from 2005 to 2020,this paper first measured green total factor productivity(GTFP)and the coordinated development index(CDIFDI)of IFDI and OFDI via the slacks-based measureglobal Malmquist–Luenberger(SBM-GML)model and the capacity coupling model.A panel threshold model with interactive effects(PTIFEs)was then applied to explore the nonlinear impact of the CDIFDI on China’s GTFP.Finally,a regional heterogeneity analysis was conducted for China’s eastern,central and western regions of China.Results show that(1)GTFP in China kept rising with small fluctuations during the sample period,with the increasing range of GTFP decreasing from east to west.(2)CDIFDI had a significant“U”-shaped threshold effect on GTFP,and the main threshold variables were the industrial structure and the level of economic development.(3)CDIFDI played a positive role in promoting GTFP growth in the eastern region,while the effects of CDIFDI on GTFP in the central and western regions were not significant.Policy-makers and enterprises should comprehensively consider promoting regional industrial upgrading and economic growth to achieve a greater positive impact of CDIFDI on GTFP.Scientifically measuring GTFP and exploring the nonlinear impact of the CDIFDI on GTFP and regional heterogeneity provide helpful references for policy-makers to coordinate the high-quality development of regional economies.
