Scholars have a variety of theoretical explanations for housing price growth. However, few scholars have studied the internal influence mechanism among urbanization, land finance, and housing price. Based on the data ...Scholars have a variety of theoretical explanations for housing price growth. However, few scholars have studied the internal influence mechanism among urbanization, land finance, and housing price. Based on the data of 182 prefecture-level cities from 2009 to 2016, this paper studies the influence of land finance on housing price under different urbanization rate levels. The study finds that with the increase of urbanization rate, the effect of land finance on housing price presents a "U" shape.Specifically, an increase in land finance by 1% results in a corresponding increase in average housing price by 0.18%, with relatively low urbanization rate, 0.06% with medium level of urbanization rate,and 0.38% with high level of urbanization rate.展开更多
In this review, we highlight some recent methodological and theoretical develop- ments in estimation and testing of large panel data models with cross-sectional dependence. The paper begins with a discussion of issues...In this review, we highlight some recent methodological and theoretical develop- ments in estimation and testing of large panel data models with cross-sectional dependence. The paper begins with a discussion of issues of cross-sectional dependence, and introduces the concepts of weak and strong cross-sectional dependence. Then, the main attention is primarily paid to spatial and factor approaches for modeling cross-sectional dependence for both linear and nonlinear （nonparametric and semiparametric） panel data models. Finally, we conclude with some speculations on future research directions.展开更多
Objective To study the causal relationship between R&D investment and enterprise performance of domestic pharmaceutical enterprises.Methods Panel data model was adopted for empirical analysis.Results and Conclusio...Objective To study the causal relationship between R&D investment and enterprise performance of domestic pharmaceutical enterprises.Methods Panel data model was adopted for empirical analysis.Results and Conclusion Increasing the R&D investment intensity of pharmaceutical enterprises in the Yangtze River Delta and Zhejiang by 1%will increase their profit margins by 0.79%and 0.46%.On the contrary,if the profit margin increases by 1%,the R&D investment intensity will increase by 0.25%and 0.19%.If the profit margin of pharmaceutical enterprises in Beijing,Tianjin,Hebei,Chengdu,Chongqing and other regions increases by 1%,the R&D investment intensity will increase by 0.14%,0.07%and 0.1%,respectively,which are lower than those in the Yangtze River Delta and Zhejiang.The relationship between R&D investment and enterprise performance of pharmaceutical enterprises in the Yangtze River Delta and Zhejiang Province is Granger causality,showing a two-way positive effect.Profits and R&D investment of pharmaceutical enterprises in Beijing,Tianjin,Hebei,Chengdu,Chongqing and other regions are also Granger causality.But in the Pearl River Delta,profits and R&D investment have not passed the stability test,it is impossible to determine the causality between them.展开更多
Currently,more than ten ultrahigh arch dams have been constructed or are being constructed in China.Safety control is essential to long-term operation of these dams.This study employed the flexibility coefficient and ...Currently,more than ten ultrahigh arch dams have been constructed or are being constructed in China.Safety control is essential to long-term operation of these dams.This study employed the flexibility coefficient and plastic complementary energy norm to assess the structural safety of arch dams.A comprehensive analysis was conducted,focusing on differences among conventional methods in characterizing the structural behavior of the Xiaowan arch dam in China.Subsequently,the spatiotemporal characteristics of the measured performance of the Xiaowan dam were explored,including periodicity,convergence,and time-effect characteristics.These findings revealed the governing mechanism of main factors.Furthermore,a heterogeneous spatial panel vector model was developed,considering both common factors and specific factors affecting the safety and performance of arch dams.This model aims to comprehensively illustrate spatial heterogeneity between the entire structure and local regions,introducing a specific effect quantity to characterize local deformation differences.Ultimately,the proposed model was applied to the Xiaowan arch dam,accurately quantifying the spatiotemporal heterogeneity of dam performance.Additionally,the spatiotemporal distri-bution characteristics of environmental load effects on different parts of the dam were reasonably interpreted.Validation of the model prediction enhances its credibility,leading to the formulation of health diagnosis criteria for future long-term operation of the Xiaowan dam.The findings not only enhance the predictive ability and timely control of ultrahigh arch dams'performance but also provide a crucial basis for assessing the effectiveness of engineering treatment measures.展开更多
The present paper reviews the vibro-acoustic modelling of extruded aluminium train floor structures including the state-of-the-art of its industrial applications, as well as the most recent developments on mid-frequen...The present paper reviews the vibro-acoustic modelling of extruded aluminium train floor structures including the state-of-the-art of its industrial applications, as well as the most recent developments on mid-frequency mod- elling techniques in general. With the common purpose to predict mid-frequency vibro-acoustic responses of stiffened panel structures to an acceptable accuracy at a reasonable computational cost, relevant techniques are mainly based on one of the following three types of mid-frequency vibro- acoustic modelling principles： （1） enhanced deterministic methods, （2） enhanced statistical methods, and （3） hybrid deterministic/statistical methods. It is shown that, although recent developments have led to a significant step forward in industrial applicability, mature and adequate prediction tech- niques, however, are still very much required for solving sound transmission through, and radiation from, extruded aluminium panels used on high-speed trains. Due to their great potentials for predicting mid-frequency vibro-acoustics of stiffened panel structures, two of recently developed mid-frequency modelling approaches, i.e. the so-called hybrid finite element-statistical energy analysis （FE-SEA） and hybrid wave-based method- statistical energy analysis （WBM-SEA）, are then recapitulated.展开更多
Green technology innovation is an important driving force and source to promote my country’s high-quality development,and it is the core path to achieve sustainable development.This paper uses my country’s provincia...Green technology innovation is an important driving force and source to promote my country’s high-quality development,and it is the core path to achieve sustainable development.This paper uses my country’s provincial panel data from 2016 to 2019 to study the impact mechanism of R&D investment on green technology innovation,and introduces the level of digitization,using the panel threshold model to discuss its role in the impact mechanism of R&D investment on green technology innovation.The study found that when the level of digitalization in a region is low,increasing R&D investment does not necessarily improve the ability of green technology innovation;when the level of digitalization is relatively high,R&D investment has a positive role in promoting green technology innovation.Therefore,it is necessary to improve policies to encourage enterprises to increase investment in research and development;at the same time,it is necessary to promote the coordinated development of digital foundation,digital investment,digital literacy,digital economy and digital application,and promote the deep integration of digitalization and green technology innovation.展开更多
Airline passenger volume is an important reference for the implementation of aviation capacity and route adjustment plans.This paper explores the determinants of airline passenger volume and proposes a comprehensive p...Airline passenger volume is an important reference for the implementation of aviation capacity and route adjustment plans.This paper explores the determinants of airline passenger volume and proposes a comprehensive panel data model for predicting volume.First,potential factors influencing airline passenger volume are analyzed from Geo-economic and service-related aspects.Second,the principal component analysis(PCA)is applied to identify key factors that impact the airline passenger volume of city pairs.Then the panel data model is estimated using 120 sets of data,which are a collection of observations for multiple subjects at multiple instances.Finally,the airline data from Chongqing to Shanghai,from 2003 to 2012,was used as a test case to verify the validity of the prediction model.Results show that railway and highway transportation assumed a certain proportion of passenger volumes,and total retail sales of consumer goods in the departure and arrival cities are significantly associated with airline passenger volume.According to the validity test results,the prediction accuracies of the model for 10 sets of data are all greater than 90%.The model performs better than a multivariate regression model,thus assisting airport operators decide which routes to adjust and which new routes to introduce.展开更多
On the basis of using entropy weight method to measure China’s education poverty alleviation and rural revitalization evaluation indicators, using the panel data of 30 provinces in China (excluding Xizang, Hong Kong,...On the basis of using entropy weight method to measure China’s education poverty alleviation and rural revitalization evaluation indicators, using the panel data of 30 provinces in China (excluding Xizang, Hong Kong, Macao and Taiwan) from 2012 to 2021, a spatial panel simultaneous equation model is constructed based on adjacency matrix, geographical distance matrix and economic geographical distance matrix deeply study the interaction mechanism and spatial spillover effects between education poverty alleviation and rural revitalization through the generalized spatial three-stage least squares method (GS3SLS). The results indicate that there is a significant spatial spillover effect and a positive spatial correlation between education poverty alleviation and rural revitalization, and there is a significant interactive effect between the two variables, while promoting each other positively. Therefore, the government should clarify the deep relationship between education poverty alleviation and rural revitalization based on the current background, and better consolidate and expand the effective connection between the achievements of education poverty alleviation and rural revitalization.展开更多
Under the“dual carbon”goal,local governments in China have strategically focused on enhancing capital utilization efficiency and enforcing environmental regulations to improve carbon emission performance.This dual a...Under the“dual carbon”goal,local governments in China have strategically focused on enhancing capital utilization efficiency and enforcing environmental regulations to improve carbon emission performance.This dual approach targets the intertwined challenges of economic development and environmental protection.Utilizing data from 266 prefecture-level cities in China from 2007 to 2019,this study systematically investigates the effects of capital matching and environmental regulation on carbon emission performance through the spatial Durbin model and the instrumental variable method.The results indicate that both capital matching and environmental regulation significantly enhance carbon emission performance.Capital matching demonstrates positive spatial spillover effects,whereas environmental regulation exhibits negative spatial spillover effects.Furthermore,there are synergistic effects between capital matching and environmental regulation that jointly enhance carbon emission performance.To address potential biases caused by endogenous environmental regulation,the study uses the proportion of environment-related words in provincial government work reports as an instrumental variable for environmental regulation.Additionally,to capture the heterogeneity in the environmental governance willingness and intensity of prefecture-level municipal governments,the study constructs heterogeneous instrumental variables.These variables are derived by multiplying the proportion of a prefecture-level city’s total industrial output value to the province’s total industrial output value with the proportion of environment-related words in the provincial government work reports.Analyses based on these instrumental variables reveal that endogenous issues in environmental regulation lead to an overestimation of its positive impact on carbon emission performance.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
Background:Adolescent depression and school refusal(SR)are prevalent and important global concerns that need to be understood and addressed.Cross-sectional associations have been reported but prospective relationships...Background:Adolescent depression and school refusal(SR)are prevalent and important global concerns that need to be understood and addressed.Cross-sectional associations have been reported but prospective relationships between them remain unclear.This longitudinal study investigated the bidirectional relationships between these two problems among Chinese adolescents.Methods:A longitudinal study was conducted in Taizhou,China,surveying students of three junior high schools,three senior high schools,and one vocational high school.A total of 3882 students completed the questionnaire at baseline(T1);3167 of them completed an identical follow-up questionnaire after 6 months(T2).Depression was assessed via the Patient Health Questionnaire(PHQ-9)and SR via the modified Chinese version of The School Refusal Assessment Scale-Revised(SRAS-R).Cross-lagged panel modeling(CLPM)analysis was conducted to test the reciprocal relationships,adjusting for socio-demographic factors.Multiple group analysis was conducted to test whether the CLPM differed by gender and grade.Results:Statistically significant bidirectional relationships were found.A higher level of SR assessed at T1 is prospectively associated with a higher level of depression at T2(β=0.07,p=0.006);a higher level of depression at T1 also is prospectively associated with a higher level of SR at T2(β=0.14,p<0.001).Such models differed significantly by neither gender nor grade.Conclusion:SR and depression should be seen as each other’s mutually reinforcing association.The bidirectional relationships potentially result in a vicious cycle.Early interventions may target both problems concurrently.Future studies may involve more time points and test some mediators.展开更多
The sustainable development has been seriously challenged by global climate change due to carbon emissions. As a developing country, China promised to reduce 40%-45% below the level of the year 2005 on its carbon inte...The sustainable development has been seriously challenged by global climate change due to carbon emissions. As a developing country, China promised to reduce 40%-45% below the level of the year 2005 on its carbon intensity by 2020. The realization of this target depends on not only the substantive transition of society and economy at the national scale, but also the action and share of energy saving and emissions reduction at the provincial scale. Based on the method provided by the IPCC, this paper examines the spati- otemporal dynamics and dominating factors of China＇s carbon intensity from energy con- sumption in 1997-2010. The aim is to provide scientific basis for policy making on energy conservation and carbon emission reduction in China. The results are shown as follows. Firstly, China＇s carbon emissions increased from 4.16 Gt to 11.29 Gt from 1997 to 2010, with an annual growth rate of 7.15%, which was much lower than that of GDP （11.72%）. Secondly, the trend of Moran＇s I indicated that China＇s carbon intensity has a growing spatial agglom- eration at the provincial scale. The provinces with either high or low values appeared to be path-dependent or space-locked to some extent. Third, according to spatial panel economet- ric model, energy intensity, energy structure, industrial structure and urbanization rate were the dominating factors shaping the spatiotemporal patterns of China＇s carbon intensity from energy consumption. Therefore, in order to realize the targets of energy conservation and emission reduction, China should improve the efficiency of energy utilization, optimize energy and industrial structure, choose the low-carbon urbanization approach and implement regional cooperation strategy of energy conservation and emissions reduction.展开更多
Enhancing the economic resilience of agriculture is essential for promoting sustainable and high-quality agricultural development.The emergence of digital technology has created new opportunities in this field.However...Enhancing the economic resilience of agriculture is essential for promoting sustainable and high-quality agricultural development.The emergence of digital technology has created new opportunities in this field.However,existing research predominantly focuses on traditional agricultural factors and technologies.Therefore,the impact of digital technology on agricultural economic resilience within the broader context of the“production-operation-industry”system in agriculture has not been comprehensively explored.To bridge this gap,this study analyzes panel data from 30 Chinese provinces from 2011 to 2020.It employs the static Van Dorn’s law and a dynamic spatial panel model to examine how digital technology empowers agricultural resilience.The findings indicate a continuous strengthening of digital technology development in China,albeit with significant polarization and spatial imbalances.Moreover,the resilience of the agricultural economy undergoes notable fluctuations,initially narrowing and subsequently displaying an upward trend.Digital technology clearly plays a pivotal role in empowering resilience through agricultural scale operation,industrial transformation,and technological progress.Its impact,particularly on the promotion of resilience in the eastern region and non-grain-producing areas and on high-level agricultural economies,also shows regional and technological variations.展开更多
Improving cultivated land use eco-efficiency(CLUE)can effectively promote agricultural sustainability,particularly in developing countries where CLUE is generally low.This study used provincial-level data from China t...Improving cultivated land use eco-efficiency(CLUE)can effectively promote agricultural sustainability,particularly in developing countries where CLUE is generally low.This study used provincial-level data from China to evaluate the spatiotemporal evolution of CLUE from 2000 to 2020 and identified the influencing factors of CLUE by using a panel Tobit model.In addition,given the undesirable outputs of agricultural production,we incorporated carbon emissions and nonpoint source pollution into the global benchmark-undesirable output-super efficiency-slacks-based measure(GB-US-SBM)model,which combines global benchmark technology,undesirable output,super efficiency,and slacks-based measure.The results indicated that there was an upward trend in CLUE in China from 2000 to 2020,with an increase rate of 2.62%.The temporal evolution of CLUE in China could be classified into three distinct stages:a period of fluctuating decrease(2000-2007),a phase of gradual increase(2008-2014),and a period of rapid growth(2015-2020).The major grain-producing areas(MPAs)had a lower CLUE than their counterparts,namely,non-major grain-production areas(non-MPAs).The spatial agglomeration effect followed a northeast-southwest strip distribution;and the movement path of barycentre revealed a"P"shape,with Luoyang City,Henan Province,as the centre.In terms of influencing factors of CLUE,investment in science and technology played the most vital role in improving CLUE,while irrigation index had the most negative effect.It should be noted that these two influencing factors had different impacts on MPAs and non-MPAs.Therefore,relevant departments should formulate policies to enhance the level of science and technology,improve irrigation condition,and promote sustainable utilization of cultivated land.展开更多
Taking the aquaculture area, the number of farming boats and that of aquaculturist as input variables, the aquaculture production as desirable output variable and polluted economic loss as undesirable output variable,...Taking the aquaculture area, the number of farming boats and that of aquaculturist as input variables, the aquaculture production as desirable output variable and polluted economic loss as undesirable output variable, this paper conducts SBM model to evaluate the aquaculture efficiency based on the data of 16 aquaculture-developed provinces in China from 2004 to 2011. The results show the efficiency in China has not changed much in recent years with the efficiency values mainly between 0.39 and 0.53, and the efficiency of marine-aquaculture-dominated provinces is generally higher than that of freshwater-aquaculture-dominated ones. To analyze the difference under the efficiency, the panel Tobit model is used with education level factor, training factor, technology extension factor, technical level factor, scale factor and species factor as the efficiency influencing factors. The results show that technology extension factor and technical level factor have significant positive influence.展开更多
This paper proposes to use DEA models with undesirable outputs to construct the Malmquist index that can be use to investigate the dynamic changes of CO 2 emission performance.With the index,the authors have measured ...This paper proposes to use DEA models with undesirable outputs to construct the Malmquist index that can be use to investigate the dynamic changes of CO 2 emission performance.With the index,the authors have measured the CO 2 emission performance of 28 provinces and autonomous regions in China from 1996 to 2007;with the convergence theory and panel data regression model,the authors analyze the regional differences and the influencing factors.It is found that the performance of CO 2 emissions in China has been continuously improved mainly due to the technological progress,and the average improvement rate is 3.25%,with a cumulative improvement rate of 40.86%.In addition,the CO 2 emission performance varies across four regions.As a whole,the performance score of eastern China is the highest.The northeastern and central China has relatively lower performance scores,and the western China is relatively backward.The regional differences are decreasing,and the performance of CO 2 emissions is convergent.The influence of some factors on the performance of CO 2 emissions is significant,such as the level of economic development,the level of industrial structure,energy intensity,and ownership structure.The influence of some factors,such as opening-up to the outside world,on the performance of CO 2 emissions is not significant..展开更多
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 e...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.展开更多
In order to practice the concept of‘lucid waters and lush mountains are invaluable assets’and promote the green development of agriculture,it is necessary to improve the efficiency of agricultural energy utilization...In order to practice the concept of‘lucid waters and lush mountains are invaluable assets’and promote the green development of agriculture,it is necessary to improve the efficiency of agricultural energy utilization.Based on the panel data of 28 provinces from 1995 to 2018,this paper calculated China’s agricultural energy input from two categories of direct energy and indirect energy,and used EBM(Epsilon-based Measure)mixed distance function model to measure the energy efficiency of agriculture in China.The nuclear density function and spatial autocorrelation were used to analyze the dynamic evolution of agricultural energy efficiency,and the dynamic panel model was used to analyze the influencing factors of agricultural energy efficiency.The results showed that:①From 1995 to 2018,the total agricultural energy input had increased year by year in China,with an average annual growth rate of 2%.Energy input structure changed from indirect energy-based to direct energy-based.Agricultural energy efficiency showed an evolutionary trend of‘rising-stagnating-rising rapidly’in China.The agricultural energy efficiency was generally low in China,and there was a large space for improvement in agricultural energy efficiency.②From 1995 to 2018,the average annual growth rate of agricultural energy efficiency in the eastern,central and western regions was 2.7%,1.9%and 1.4%respectively.In 2018,the agricultural energy efficiency in the eastern,central and western regions was 0.81,0.71 and 0.59 respectively.The gap between regions was expanding rapidly,and the agricultural energy efficiency in the central and western regions needed to be improved.③From 1995 to 2018,the agricultural energy efficiency of each province was polarized and the absolute gap was widened.There was obvious improvement in agricultural energy efficiency in Guangdong,Shandong,Jiangxi,Jiangsu,Liaoning and Tianjin,while the agricultural energy efficiency of Xinjiang,Guizhou,Zhejiang,Shanghai,and Inner Mongolia deteriorated.④From 1995 to 2018,there was no global spatial correlation of China’s agricultural energy efficiency.However,local‘high-high’concentration gradually appeared in the eastern region since 2010.⑤The first lag of energy efficiency had a significant positive impact on agricultural energy efficiency,and agricultural energy efficiency improvement had a time lag.The level of human capital,per capita net income of farmers and the level of urbanizaton had a significant positive impact on agricultural energy efficiency.The disaster rate,the level of development of secondary and tertiary industries,and the level of opening up had a significant negative impact on agricultural energy efficiency.In the implementation of the strategy of rural revitalization,we should focus on the central and western regions,take the cultivation of professional farmers as the key,focus on improving agricultural production conditions,enhance the level of cooperation between regions,exert the leading role of the secondary and tertiary industries,and enhance the ability of agricultural disaster prevention and mitigation.展开更多
Impoverished sub-Saharan Africa(SSA)is under increasing environmental pressure from global environmental changes.It is now generally accepted in academic circles that economic development in SSA countries can cause en...Impoverished sub-Saharan Africa(SSA)is under increasing environmental pressure from global environmental changes.It is now generally accepted in academic circles that economic development in SSA countries can cause environmental pressure in other countries.However,there is research gap on the impact of economic assistance on environmental pressure in SSA countries and whether economic assistance causes spatial spillovers of environ-mental pressure between SSA countries.To better understand the impact of economic assistance on environmental pressures in SSA,a dynamic spatial Dubin panel model was developed.It helped us explore the spatial spillover effects of economic assistance on environmental pressures in recipient countries based on the panel data from 34 SSA countries.The results show that economic assistance had a positive stimulating effect on environmen-tal pressures of recipient countries,which means that the degree of human disturbance to the environment has deepened.Due to the regional correlation effect,neighboring countries were saddled with environmental pres-sures from the target country.Moreover,environmental pressures have time inertia,which can easily produce a snowball effect.The decomposition of effects shows that the impact of economic assistance on environmental pressures is relatively minor.Environmental pressures have spillover effects,so to deal with diffuse risks,joint regional prevention and control policies should be developed.展开更多
基金Supported by Natural Science Foundation of China(71850014,71532013,71573244,71974180)。
文摘Scholars have a variety of theoretical explanations for housing price growth. However, few scholars have studied the internal influence mechanism among urbanization, land finance, and housing price. Based on the data of 182 prefecture-level cities from 2009 to 2016, this paper studies the influence of land finance on housing price under different urbanization rate levels. The study finds that with the increase of urbanization rate, the effect of land finance on housing price presents a "U" shape.Specifically, an increase in land finance by 1% results in a corresponding increase in average housing price by 0.18%, with relatively low urbanization rate, 0.06% with medium level of urbanization rate,and 0.38% with high level of urbanization rate.
基金Supported by the National Natural Science Foundation of China(71131008(Key Project)and 71271179)
文摘In this review, we highlight some recent methodological and theoretical develop- ments in estimation and testing of large panel data models with cross-sectional dependence. The paper begins with a discussion of issues of cross-sectional dependence, and introduces the concepts of weak and strong cross-sectional dependence. Then, the main attention is primarily paid to spatial and factor approaches for modeling cross-sectional dependence for both linear and nonlinear （nonparametric and semiparametric） panel data models. Finally, we conclude with some speculations on future research directions.
基金Shenyang Pharmaceutical University Young and Middle aged Teacher Career Development Support PlanPublic Welfare Research Fund for Scientific Undertakings of Liaoning Province in 2022(Soft Science Research Plan)(No.2022JH4/10100040).
文摘Objective To study the causal relationship between R&D investment and enterprise performance of domestic pharmaceutical enterprises.Methods Panel data model was adopted for empirical analysis.Results and Conclusion Increasing the R&D investment intensity of pharmaceutical enterprises in the Yangtze River Delta and Zhejiang by 1%will increase their profit margins by 0.79%and 0.46%.On the contrary,if the profit margin increases by 1%,the R&D investment intensity will increase by 0.25%and 0.19%.If the profit margin of pharmaceutical enterprises in Beijing,Tianjin,Hebei,Chengdu,Chongqing and other regions increases by 1%,the R&D investment intensity will increase by 0.14%,0.07%and 0.1%,respectively,which are lower than those in the Yangtze River Delta and Zhejiang.The relationship between R&D investment and enterprise performance of pharmaceutical enterprises in the Yangtze River Delta and Zhejiang Province is Granger causality,showing a two-way positive effect.Profits and R&D investment of pharmaceutical enterprises in Beijing,Tianjin,Hebei,Chengdu,Chongqing and other regions are also Granger causality.But in the Pearl River Delta,profits and R&D investment have not passed the stability test,it is impossible to determine the causality between them.
基金supported by the National Natural Science Foundation of China(Grant No.52079046).
文摘Currently,more than ten ultrahigh arch dams have been constructed or are being constructed in China.Safety control is essential to long-term operation of these dams.This study employed the flexibility coefficient and plastic complementary energy norm to assess the structural safety of arch dams.A comprehensive analysis was conducted,focusing on differences among conventional methods in characterizing the structural behavior of the Xiaowan arch dam in China.Subsequently,the spatiotemporal characteristics of the measured performance of the Xiaowan dam were explored,including periodicity,convergence,and time-effect characteristics.These findings revealed the governing mechanism of main factors.Furthermore,a heterogeneous spatial panel vector model was developed,considering both common factors and specific factors affecting the safety and performance of arch dams.This model aims to comprehensively illustrate spatial heterogeneity between the entire structure and local regions,introducing a specific effect quantity to characterize local deformation differences.Ultimately,the proposed model was applied to the Xiaowan arch dam,accurately quantifying the spatiotemporal heterogeneity of dam performance.Additionally,the spatiotemporal distri-bution characteristics of environmental load effects on different parts of the dam were reasonably interpreted.Validation of the model prediction enhances its credibility,leading to the formulation of health diagnosis criteria for future long-term operation of the Xiaowan dam.The findings not only enhance the predictive ability and timely control of ultrahigh arch dams'performance but also provide a crucial basis for assessing the effectiveness of engineering treatment measures.
基金sponsored by the NationalNatural foundation of China(Grant Nos.U1434201 and 51175300)
文摘The present paper reviews the vibro-acoustic modelling of extruded aluminium train floor structures including the state-of-the-art of its industrial applications, as well as the most recent developments on mid-frequency mod- elling techniques in general. With the common purpose to predict mid-frequency vibro-acoustic responses of stiffened panel structures to an acceptable accuracy at a reasonable computational cost, relevant techniques are mainly based on one of the following three types of mid-frequency vibro- acoustic modelling principles： （1） enhanced deterministic methods, （2） enhanced statistical methods, and （3） hybrid deterministic/statistical methods. It is shown that, although recent developments have led to a significant step forward in industrial applicability, mature and adequate prediction tech- niques, however, are still very much required for solving sound transmission through, and radiation from, extruded aluminium panels used on high-speed trains. Due to their great potentials for predicting mid-frequency vibro-acoustics of stiffened panel structures, two of recently developed mid-frequency modelling approaches, i.e. the so-called hybrid finite element-statistical energy analysis （FE-SEA） and hybrid wave-based method- statistical energy analysis （WBM-SEA）, are then recapitulated.
文摘Green technology innovation is an important driving force and source to promote my country’s high-quality development,and it is the core path to achieve sustainable development.This paper uses my country’s provincial panel data from 2016 to 2019 to study the impact mechanism of R&D investment on green technology innovation,and introduces the level of digitization,using the panel threshold model to discuss its role in the impact mechanism of R&D investment on green technology innovation.The study found that when the level of digitalization in a region is low,increasing R&D investment does not necessarily improve the ability of green technology innovation;when the level of digitalization is relatively high,R&D investment has a positive role in promoting green technology innovation.Therefore,it is necessary to improve policies to encourage enterprises to increase investment in research and development;at the same time,it is necessary to promote the coordinated development of digital foundation,digital investment,digital literacy,digital economy and digital application,and promote the deep integration of digitalization and green technology innovation.
基金The National Natural Science Fund of China(No.U1564201 and No.U51675235).
文摘Airline passenger volume is an important reference for the implementation of aviation capacity and route adjustment plans.This paper explores the determinants of airline passenger volume and proposes a comprehensive panel data model for predicting volume.First,potential factors influencing airline passenger volume are analyzed from Geo-economic and service-related aspects.Second,the principal component analysis(PCA)is applied to identify key factors that impact the airline passenger volume of city pairs.Then the panel data model is estimated using 120 sets of data,which are a collection of observations for multiple subjects at multiple instances.Finally,the airline data from Chongqing to Shanghai,from 2003 to 2012,was used as a test case to verify the validity of the prediction model.Results show that railway and highway transportation assumed a certain proportion of passenger volumes,and total retail sales of consumer goods in the departure and arrival cities are significantly associated with airline passenger volume.According to the validity test results,the prediction accuracies of the model for 10 sets of data are all greater than 90%.The model performs better than a multivariate regression model,thus assisting airport operators decide which routes to adjust and which new routes to introduce.
文摘On the basis of using entropy weight method to measure China’s education poverty alleviation and rural revitalization evaluation indicators, using the panel data of 30 provinces in China (excluding Xizang, Hong Kong, Macao and Taiwan) from 2012 to 2021, a spatial panel simultaneous equation model is constructed based on adjacency matrix, geographical distance matrix and economic geographical distance matrix deeply study the interaction mechanism and spatial spillover effects between education poverty alleviation and rural revitalization through the generalized spatial three-stage least squares method (GS3SLS). The results indicate that there is a significant spatial spillover effect and a positive spatial correlation between education poverty alleviation and rural revitalization, and there is a significant interactive effect between the two variables, while promoting each other positively. Therefore, the government should clarify the deep relationship between education poverty alleviation and rural revitalization based on the current background, and better consolidate and expand the effective connection between the achievements of education poverty alleviation and rural revitalization.
文摘Under the“dual carbon”goal,local governments in China have strategically focused on enhancing capital utilization efficiency and enforcing environmental regulations to improve carbon emission performance.This dual approach targets the intertwined challenges of economic development and environmental protection.Utilizing data from 266 prefecture-level cities in China from 2007 to 2019,this study systematically investigates the effects of capital matching and environmental regulation on carbon emission performance through the spatial Durbin model and the instrumental variable method.The results indicate that both capital matching and environmental regulation significantly enhance carbon emission performance.Capital matching demonstrates positive spatial spillover effects,whereas environmental regulation exhibits negative spatial spillover effects.Furthermore,there are synergistic effects between capital matching and environmental regulation that jointly enhance carbon emission performance.To address potential biases caused by endogenous environmental regulation,the study uses the proportion of environment-related words in provincial government work reports as an instrumental variable for environmental regulation.Additionally,to capture the heterogeneity in the environmental governance willingness and intensity of prefecture-level municipal governments,the study constructs heterogeneous instrumental variables.These variables are derived by multiplying the proportion of a prefecture-level city’s total industrial output value to the province’s total industrial output value with the proportion of environment-related words in the provincial government work reports.Analyses based on these instrumental variables reveal that endogenous issues in environmental regulation lead to an overestimation of its positive impact on carbon emission performance.
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.
基金funded by Science and Technology Program of Wenzhou(Y20220843).
文摘Background:Adolescent depression and school refusal(SR)are prevalent and important global concerns that need to be understood and addressed.Cross-sectional associations have been reported but prospective relationships between them remain unclear.This longitudinal study investigated the bidirectional relationships between these two problems among Chinese adolescents.Methods:A longitudinal study was conducted in Taizhou,China,surveying students of three junior high schools,three senior high schools,and one vocational high school.A total of 3882 students completed the questionnaire at baseline(T1);3167 of them completed an identical follow-up questionnaire after 6 months(T2).Depression was assessed via the Patient Health Questionnaire(PHQ-9)and SR via the modified Chinese version of The School Refusal Assessment Scale-Revised(SRAS-R).Cross-lagged panel modeling(CLPM)analysis was conducted to test the reciprocal relationships,adjusting for socio-demographic factors.Multiple group analysis was conducted to test whether the CLPM differed by gender and grade.Results:Statistically significant bidirectional relationships were found.A higher level of SR assessed at T1 is prospectively associated with a higher level of depression at T2(β=0.07,p=0.006);a higher level of depression at T1 also is prospectively associated with a higher level of SR at T2(β=0.14,p<0.001).Such models differed significantly by neither gender nor grade.Conclusion:SR and depression should be seen as each other’s mutually reinforcing association.The bidirectional relationships potentially result in a vicious cycle.Early interventions may target both problems concurrently.Future studies may involve more time points and test some mediators.
基金Key Research Program of the Chinese Academy of Sciences, No.KZZD-EW-06-03 No.KSZD-EW-Z-021-03+2 种基金 Key Project of Chinese Ministry of Education, No. 13JJD790008 National Natural Science Foundation of China, No.41329001 No.41071108
文摘The sustainable development has been seriously challenged by global climate change due to carbon emissions. As a developing country, China promised to reduce 40%-45% below the level of the year 2005 on its carbon intensity by 2020. The realization of this target depends on not only the substantive transition of society and economy at the national scale, but also the action and share of energy saving and emissions reduction at the provincial scale. Based on the method provided by the IPCC, this paper examines the spati- otemporal dynamics and dominating factors of China＇s carbon intensity from energy con- sumption in 1997-2010. The aim is to provide scientific basis for policy making on energy conservation and carbon emission reduction in China. The results are shown as follows. Firstly, China＇s carbon emissions increased from 4.16 Gt to 11.29 Gt from 1997 to 2010, with an annual growth rate of 7.15%, which was much lower than that of GDP （11.72%）. Secondly, the trend of Moran＇s I indicated that China＇s carbon intensity has a growing spatial agglom- eration at the provincial scale. The provinces with either high or low values appeared to be path-dependent or space-locked to some extent. Third, according to spatial panel economet- ric model, energy intensity, energy structure, industrial structure and urbanization rate were the dominating factors shaping the spatiotemporal patterns of China＇s carbon intensity from energy consumption. Therefore, in order to realize the targets of energy conservation and emission reduction, China should improve the efficiency of energy utilization, optimize energy and industrial structure, choose the low-carbon urbanization approach and implement regional cooperation strategy of energy conservation and emissions reduction.
基金the National Social Science Foundation[Grant No.21&ZD101]:Research on the Implementation Path and Policy System of High-quality Development of China’s Food Industrythe National Social Science Foundation[Grant No.BGL167]:Research on the Green Benefit Sharing Mechanism of Ecological Protection in the Yangtze River Basin(2021-2024)for its support.
文摘Enhancing the economic resilience of agriculture is essential for promoting sustainable and high-quality agricultural development.The emergence of digital technology has created new opportunities in this field.However,existing research predominantly focuses on traditional agricultural factors and technologies.Therefore,the impact of digital technology on agricultural economic resilience within the broader context of the“production-operation-industry”system in agriculture has not been comprehensively explored.To bridge this gap,this study analyzes panel data from 30 Chinese provinces from 2011 to 2020.It employs the static Van Dorn’s law and a dynamic spatial panel model to examine how digital technology empowers agricultural resilience.The findings indicate a continuous strengthening of digital technology development in China,albeit with significant polarization and spatial imbalances.Moreover,the resilience of the agricultural economy undergoes notable fluctuations,initially narrowing and subsequently displaying an upward trend.Digital technology clearly plays a pivotal role in empowering resilience through agricultural scale operation,industrial transformation,and technological progress.Its impact,particularly on the promotion of resilience in the eastern region and non-grain-producing areas and on high-level agricultural economies,also shows regional and technological variations.
基金supported by the National Natural Science Foundation of China(72373117)the Chinese Universities Scientific Fund(Z1010422003)+1 种基金the Major Project of the Key Research Base of Humanities and Social Sciences of the Ministry of Education(22JJD790052)the Qinchuangyuan Project of Shaanxi Province(QCYRCXM-2022-145).
文摘Improving cultivated land use eco-efficiency(CLUE)can effectively promote agricultural sustainability,particularly in developing countries where CLUE is generally low.This study used provincial-level data from China to evaluate the spatiotemporal evolution of CLUE from 2000 to 2020 and identified the influencing factors of CLUE by using a panel Tobit model.In addition,given the undesirable outputs of agricultural production,we incorporated carbon emissions and nonpoint source pollution into the global benchmark-undesirable output-super efficiency-slacks-based measure(GB-US-SBM)model,which combines global benchmark technology,undesirable output,super efficiency,and slacks-based measure.The results indicated that there was an upward trend in CLUE in China from 2000 to 2020,with an increase rate of 2.62%.The temporal evolution of CLUE in China could be classified into three distinct stages:a period of fluctuating decrease(2000-2007),a phase of gradual increase(2008-2014),and a period of rapid growth(2015-2020).The major grain-producing areas(MPAs)had a lower CLUE than their counterparts,namely,non-major grain-production areas(non-MPAs).The spatial agglomeration effect followed a northeast-southwest strip distribution;and the movement path of barycentre revealed a"P"shape,with Luoyang City,Henan Province,as the centre.In terms of influencing factors of CLUE,investment in science and technology played the most vital role in improving CLUE,while irrigation index had the most negative effect.It should be noted that these two influencing factors had different impacts on MPAs and non-MPAs.Therefore,relevant departments should formulate policies to enhance the level of science and technology,improve irrigation condition,and promote sustainable utilization of cultivated land.
基金supported by the Major State Basic Research Development Program of China: the Research on the Key Technology of Clean and High Efficient Mariculture Pond (Grant Nos. 2011BAD 13B03)Promotive Research Fund for Excellent Young and Middle-Aged Scientists of Shandong Province: High Efficiency and Low Carbon Development Research of Shandong Mariculture Industry (Grant Nos. BS2012HZ 024)the Research of Chinese Mariculture Industry High Efficiency and Low Carbon Development Model Implementation Mechanism Funded by the Marine Development Institute of Ocean University of China Humanities and Social Science Key Research Base of Ministry of Education (Grant Nos. 2012JDZS02)
文摘Taking the aquaculture area, the number of farming boats and that of aquaculturist as input variables, the aquaculture production as desirable output variable and polluted economic loss as undesirable output variable, this paper conducts SBM model to evaluate the aquaculture efficiency based on the data of 16 aquaculture-developed provinces in China from 2004 to 2011. The results show the efficiency in China has not changed much in recent years with the efficiency values mainly between 0.39 and 0.53, and the efficiency of marine-aquaculture-dominated provinces is generally higher than that of freshwater-aquaculture-dominated ones. To analyze the difference under the efficiency, the panel Tobit model is used with education level factor, training factor, technology extension factor, technical level factor, scale factor and species factor as the efficiency influencing factors. The results show that technology extension factor and technical level factor have significant positive influence.
基金financial support provided by the National Social Science Foundation of China (Grant No. 08 &ZD046)National Natural Science Foundation of China (Grant No.70903031 and 41071348)
文摘This paper proposes to use DEA models with undesirable outputs to construct the Malmquist index that can be use to investigate the dynamic changes of CO 2 emission performance.With the index,the authors have measured the CO 2 emission performance of 28 provinces and autonomous regions in China from 1996 to 2007;with the convergence theory and panel data regression model,the authors analyze the regional differences and the influencing factors.It is found that the performance of CO 2 emissions in China has been continuously improved mainly due to the technological progress,and the average improvement rate is 3.25%,with a cumulative improvement rate of 40.86%.In addition,the CO 2 emission performance varies across four regions.As a whole,the performance score of eastern China is the highest.The northeastern and central China has relatively lower performance scores,and the western China is relatively backward.The regional differences are decreasing,and the performance of CO 2 emissions is convergent.The influence of some factors on the performance of CO 2 emissions is significant,such as the level of economic development,the level of industrial structure,energy intensity,and ownership structure.The influence of some factors,such as opening-up to the outside world,on the performance of CO 2 emissions is not significant..
基金National Natural Science Foundation of China,No.41601151Guangdong Natural Science Foundation,No.2016A030310149
文摘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.
文摘In order to practice the concept of‘lucid waters and lush mountains are invaluable assets’and promote the green development of agriculture,it is necessary to improve the efficiency of agricultural energy utilization.Based on the panel data of 28 provinces from 1995 to 2018,this paper calculated China’s agricultural energy input from two categories of direct energy and indirect energy,and used EBM(Epsilon-based Measure)mixed distance function model to measure the energy efficiency of agriculture in China.The nuclear density function and spatial autocorrelation were used to analyze the dynamic evolution of agricultural energy efficiency,and the dynamic panel model was used to analyze the influencing factors of agricultural energy efficiency.The results showed that:①From 1995 to 2018,the total agricultural energy input had increased year by year in China,with an average annual growth rate of 2%.Energy input structure changed from indirect energy-based to direct energy-based.Agricultural energy efficiency showed an evolutionary trend of‘rising-stagnating-rising rapidly’in China.The agricultural energy efficiency was generally low in China,and there was a large space for improvement in agricultural energy efficiency.②From 1995 to 2018,the average annual growth rate of agricultural energy efficiency in the eastern,central and western regions was 2.7%,1.9%and 1.4%respectively.In 2018,the agricultural energy efficiency in the eastern,central and western regions was 0.81,0.71 and 0.59 respectively.The gap between regions was expanding rapidly,and the agricultural energy efficiency in the central and western regions needed to be improved.③From 1995 to 2018,the agricultural energy efficiency of each province was polarized and the absolute gap was widened.There was obvious improvement in agricultural energy efficiency in Guangdong,Shandong,Jiangxi,Jiangsu,Liaoning and Tianjin,while the agricultural energy efficiency of Xinjiang,Guizhou,Zhejiang,Shanghai,and Inner Mongolia deteriorated.④From 1995 to 2018,there was no global spatial correlation of China’s agricultural energy efficiency.However,local‘high-high’concentration gradually appeared in the eastern region since 2010.⑤The first lag of energy efficiency had a significant positive impact on agricultural energy efficiency,and agricultural energy efficiency improvement had a time lag.The level of human capital,per capita net income of farmers and the level of urbanizaton had a significant positive impact on agricultural energy efficiency.The disaster rate,the level of development of secondary and tertiary industries,and the level of opening up had a significant negative impact on agricultural energy efficiency.In the implementation of the strategy of rural revitalization,we should focus on the central and western regions,take the cultivation of professional farmers as the key,focus on improving agricultural production conditions,enhance the level of cooperation between regions,exert the leading role of the secondary and tertiary industries,and enhance the ability of agricultural disaster prevention and mitigation.
基金This work is supported by National Natural Science Foundation of China(Grants No.72104246,71874203).
文摘Impoverished sub-Saharan Africa(SSA)is under increasing environmental pressure from global environmental changes.It is now generally accepted in academic circles that economic development in SSA countries can cause environmental pressure in other countries.However,there is research gap on the impact of economic assistance on environmental pressure in SSA countries and whether economic assistance causes spatial spillovers of environ-mental pressure between SSA countries.To better understand the impact of economic assistance on environmental pressures in SSA,a dynamic spatial Dubin panel model was developed.It helped us explore the spatial spillover effects of economic assistance on environmental pressures in recipient countries based on the panel data from 34 SSA countries.The results show that economic assistance had a positive stimulating effect on environmen-tal pressures of recipient countries,which means that the degree of human disturbance to the environment has deepened.Due to the regional correlation effect,neighboring countries were saddled with environmental pres-sures from the target country.Moreover,environmental pressures have time inertia,which can easily produce a snowball effect.The decomposition of effects shows that the impact of economic assistance on environmental pressures is relatively minor.Environmental pressures have spillover effects,so to deal with diffuse risks,joint regional prevention and control policies should be developed.
