Since the new century,China’s mathematics curriculum reform in basic education has continued to move forward in attempts and explorations,presenting many new changes,trends,movements,and developments.Sorting out,anal...Since the new century,China’s mathematics curriculum reform in basic education has continued to move forward in attempts and explorations,presenting many new changes,trends,movements,and developments.Sorting out,analyzing,and summarizing the achievements,experiences,problems,and challenges in this journey are conducive to providing insights for the reform and development of the Chinese basic education mathematics curriculum in the new era.This paper analyses the research on mathematics education in China(1999-2024)using the visual measurement of CiteSpace knowledge mapping,hoping to provide directions for the future of mathematics education in China.展开更多
Since the Reform and Opening-up in 1978,China’s economy,society and other fields have developed very rapidly.Economic growth has achieved leapfrog development,and the three industries have achieved great development,...Since the Reform and Opening-up in 1978,China’s economy,society and other fields have developed very rapidly.Economic growth has achieved leapfrog development,and the three industries have achieved great development,but the overall industrial structure needs to be improved.At present,China’s economy has entered the“New Normal”.In order to achieve“Sound and Rapid”economic development,it is imperative to transform the industrial structure.Using econometric analysis and based on China’s economic data from 1978 to 2020,this paper explores the different impacts of three industrial sectors on economic growth.Thus it analyzes the internal mechanism of China’s economic growth.It is concluded that the contribution of the tertiary industry to the national GDP is the largest,the level of secondary industry is medium,and the primary industry is the smallest.Finally,according to the calculation results,this paper puts forward corresponding suggestions for the optimization of China’s industrial structure,in order to achieve sound and rapid development of the national economy.展开更多
The main aim of this paper is to present and emphasize the contribution of stochastic numerical methods as must tools for the modern econometric modelisation. Indeed, the stochastic numerical methods play an important...The main aim of this paper is to present and emphasize the contribution of stochastic numerical methods as must tools for the modern econometric modelisation. Indeed, the stochastic numerical methods play an important role in mathematical modelling and the econometric analysis because they model uncertainties that govern the real-world data. However these powerful tools are not well-known and understood by many economists and financial econometricians.展开更多
This article used the Cluster analysis of statistical method to separate China's 30 provinces and municipalities into three categories according to their energy consumption discrepancies and characteristics from 1985...This article used the Cluster analysis of statistical method to separate China's 30 provinces and municipalities into three categories according to their energy consumption discrepancies and characteristics from 1985 to 2007. The categories were high, moderate and low energy consumption areas and they had significant differences in energy consumption. Based on this classification, the authors analyzed the influencing factors of energy consumption in the three areas by means of panel data econometric model. The results showed that the influencing factors were obviously different. In order to support national goal of energy conservation and emission reduction, the energy measures and policies should be distinctly taken.展开更多
Room occupancy rate is a key indicator of star-rated hotel management quality. This paper takes Cobb-Douglas production function as the theoretical framework. Spatial Moran index of autocorrelation, Spatial Lag Model(...Room occupancy rate is a key indicator of star-rated hotel management quality. This paper takes Cobb-Douglas production function as the theoretical framework. Spatial Moran index of autocorrelation, Spatial Lag Model(SLM) and Spatial Error Model(SEM) are used to analyze the star-rated hotels labor productivity of 31 provincial regions in China's Mainland based on the star-rated hotels statistical data of year 2016. The spatial correlation and spatial difference of the star-rated hotels labor productivity is discussed. This paper studies the impact of three factors on spatial characteristics of star-rated hotels labor productivity in China's Mainland. The econometric estimation results show that:(1) Star-rated hotels labor productivity present significant spatial dependence and spatial difference in China's Mainland.(2) The estimation results of Ordinary least Squares(OLS) are reliable.(3) The reliability of the results obtained by the Spatial Error Model(SEM) analysis is the highest, and has a stronger explanatory power to the spatial relationship of star-rated hotels labor productivity in China's Mainland. The average room occupancy rate has more influence on the labor productivity of the provincial star-rated hotels than the impact of capital and labor.展开更多
With the intensified competition in the capital market,the continuous development of internet finance,and the gradual loosening of market regulation,the profit pressure on securities firms relying on traditional busin...With the intensified competition in the capital market,the continuous development of internet finance,and the gradual loosening of market regulation,the profit pressure on securities firms relying on traditional business is increasing.In order to seek new profit growth points,many securities firms have ventured into business diversification,but with varying results.From the perspective of enterprise operational sustainability,econometric methods are used to explore the relationship between the diversification and business performance of securities firms in China,putting forward diversification strategies suitable for these firms.展开更多
This study measured the level of innovation achievement protection and the degree of internal structural upgrading of the productive service industry in 28 provinces of China from 2000 to 2022.Exploratory spatial anal...This study measured the level of innovation achievement protection and the degree of internal structural upgrading of the productive service industry in 28 provinces of China from 2000 to 2022.Exploratory spatial analysis methods were used to test the spatial correlation between the two variables,and the spatial impact of innovation achievement protection on the optimization of the internal structure of the productive service industry was examined at the national and sectoral levels.The results showed three main aspects of this system.(1)The agglomeration level of innovation achievement protection and internal structure optimization of the productive service industry between regions in China continued to increase during the sample period,and there was a clear similarity and synchronicity in the spatial evolution of the two variables.(2)The overall improvement in the protection level of innovative achievements is conducive to promoting the internal structural upgrading of China’s productive service industry.However,there are significant differences in the degree to which the protection of innovative achievements affects the internal structural upgrading of the productive service industry in the four major regions of the East,Central,Northeast,and West.The protection of innovative achievements in the East and Central regions significantly promotes the internal structural optimization of the productive service industry,while this effect is not significant in the western and northeastern regions.(3)The results of the robustness test indicate that the impact of internal structural upgrading of the productive service industry in the previous year on the level of innovation achievement protection is not significant.The interference from abnormal values of the internal structural upgrading of the productive service industry in various regions and the influence of municipalities directly under the central government on the regression results are not significant.After replacing the main variable,the coefficient of the innovation achievement protection level remained significantly positive.The conclusions of this study supplement and improve the theory of innovation achievement protection and industrial transformation and upgrading,providing decision-making support for improving the level of innovation achievement protection and promoting the internal structural upgrading of the productive service industries in China.展开更多
Urban agglomeration plays a vital role in fostering high-quality and sustainable development in China,where urbanization rates signifi-cantly influence both urban and rural environments,generating different economic a...Urban agglomeration plays a vital role in fostering high-quality and sustainable development in China,where urbanization rates signifi-cantly influence both urban and rural environments,generating different economic and socio-spatial impacts that,in turn,influence carbon emissions in cities.To delve into the influencing mechanisms of carbon emissions,this paper examines the spatio-temporal pattern of carbon emissions across 41 cities in the Yangtze River Delta urban agglomeration in China.It utilizes data on economic,social,and spatial factors from 2012 to 2019 and employs a spatial econometric regression model for analysis.The results indicate that carbon emissions of cities in the urban agglomeration exhibited strong spatial correlation from 2012 to 2019,characterized by relatively stable cold and hot spots,along with continuous outward spread of high-value zones.Economic and social factors demonstrate a significant positive spatial correlation with carbon emissions of a city,with weak spatial spillover effects.Spatial factors exhibit correlations with carbon emissions in both the city and neighboring cities,with strong spatial spillover effects.Moreover,the spatial layout and functional division of cities in the urban agglomeration also significantly impact the spatio-temporal pattern of carbon emissions.展开更多
In order to explore the factors and their complex mechanism affecting the price dynamics under the clean development mechanism (CDM), this article employs the secondary Certified Emission Reduction (sCER) carbon p...In order to explore the factors and their complex mechanism affecting the price dynamics under the clean development mechanism (CDM), this article employs the secondary Certified Emission Reduction (sCER) carbon price as the study object, and analyzes its influencing factors from aspects of the international carbon-reduction policies, macroeconomic fluctuations, energy and similar carbon products prices. The innovation of this paper lies in: Introducing necessary factor (the developing countries pricing power) and the application of several international representative indicators to un- derline the "world" nature of CDM; utilizing different econometric models to obtain noteworthy and more robust results. The authors test the theoretical findings with multiple stationary time series from the launch of CDM to present (2008-2016). The results reveal that sCER price fluctuation shows the characteristic of asymmetry and substantial persistence. There is a strong statistically significant relationship between macroeconomic conditions, coal and oil prices, with the price of sCER. The authors discover that the pricing power of developing countries indeed has a clear but small impact on the sCER price changes, whereas the price elasticity of supply under CDM is so weak. The interaction between EU emission allowances (EUAs) and sCER presents a shift from dependency to substitution.展开更多
Rural decline has become a global problem.To address this issue,the division of rural functions and identification of driving factors are important means of rural revitalization.Taking the town area as a unit,this stu...Rural decline has become a global problem.To address this issue,the division of rural functions and identification of driving factors are important means of rural revitalization.Taking the town area as a unit,this study conducts a division and evolution analysis of rural regional functions in Jiangsu province in coastal China by constructing an evaluation system using the spatial econometric model to diagnose endogenous and exogenous driving factors of rural multifunction formation.The results show that the functions of agricultural supply and ecological conservation have decreased,while the functions of economic development and social security have increased.Agricultural production functions are concentrated in northern and central Jiangsu.The economic development function is mainly based on industrial development,and is the strongest in southern Jiangsu.Social security functions are concentrated in suburban area,county centers,and key towns.High-value areas of ecological conservation are concentrated along lakes,the coast,and hilly areas of southern Jiangsu.The multifunctional development of villages and towns is affected by endogenous and exogenous factors,including economic geographic location,natural resources,economic foundation,human capital,traffic conditions,market demand,infrastructure,and environmental governance.Natural factors have a significant impact on the supply of agricultural products and the formation of ecological conservation functions.The effects of socioeconomic factors on these four functions differ significantly.This study expands the theory of rural development functions,the classification and zoning paradigm,and the quantitative study of driving mechanisms.The results provide a reference for practical value and policy significance for the reconstruction of rural functions and rural revitalization.展开更多
Village is an important implementation unit of national poverty alleviation and development strategies of rural China, and identifying the poverty degree, poverty type and poverty contributing factors of each poverty-...Village is an important implementation unit of national poverty alleviation and development strategies of rural China, and identifying the poverty degree, poverty type and poverty contributing factors of each poverty-stricken village is the precondition and guarantee of taking targeted measures in poverty alleviation strategies of China. To respond it, we construct a village-level multidimensional poverty measuring model, and use indicator contribution degree indices and linear regression method to explore poverty factors, while adopting Least Square Error(LSE) model and spatial econometric analysis model to identify the villages' poverty types and poverty difference. The case study shows that:(1) Spatially, there is obvious territoriality in the distribution of poverty-stricken villages, and the poverty-stricken villages are concentrated in contiguous poverty-stricken areas. The areas with the highest VPI, in a descending order, are Gansu, Yunnan, Guizhou, Guangxi, Hunan, Qinghai, Sichuan, and Xinjiang.(2) The main factors contributing to the poverty of poverty-stricken villages in rural China include road construction, terrain type, frequency of natural disasters, per capita net income, labor force ratio, and cultural quality of labor force. The main causes of poverty include underdeveloped road construction conditions, frequent natural disasters, low level of income, and labor conditions.(3) Chinese poverty-stricken villages include six main subtypes, and most poverty-stricken villages are affected by multiple poverty-forming factors, reflected by a relatively high proportion of the three-factor dominant type, four-factor coordinative type, and five-factor combinative type.(4) There exist significant poverty differences in terms of geographical location and policy support, and the governments still need to carry out targeted poverty alleviation measures according to local conditions. The research can not only draw a macro overall poverty-reduction outline of impoverished villages in China, but also depict the specific poverty characteristics of each village, helping the government departments of pov-erty alleviation at all levels to mobilize all kinds of anti-poverty resources.展开更多
Over the last decade, India has started to concentrate earnestly on renewable energy. The Indian government, as well as different state governments, are adopting policy instruments such as feed in tariff, captive cons...Over the last decade, India has started to concentrate earnestly on renewable energy. The Indian government, as well as different state governments, are adopting policy instruments such as feed in tariff, captive consumption, renewable purchase obligation and genera- tion based incentive etc. aimed at renewable energy development. This paper evaluates the effectiveness of state level incentives for the development of wind energy in India. Fixed effect panel data modelling technique of econometric analysis is used to analyse the data of 26 Indian states in 11 years. The results show that feed in tariff and captive consumption are the significant predictors of wind energy development. However, renewable purchase obligation does not affect wind energy significantly.展开更多
文摘Since the new century,China’s mathematics curriculum reform in basic education has continued to move forward in attempts and explorations,presenting many new changes,trends,movements,and developments.Sorting out,analyzing,and summarizing the achievements,experiences,problems,and challenges in this journey are conducive to providing insights for the reform and development of the Chinese basic education mathematics curriculum in the new era.This paper analyses the research on mathematics education in China(1999-2024)using the visual measurement of CiteSpace knowledge mapping,hoping to provide directions for the future of mathematics education in China.
文摘Since the Reform and Opening-up in 1978,China’s economy,society and other fields have developed very rapidly.Economic growth has achieved leapfrog development,and the three industries have achieved great development,but the overall industrial structure needs to be improved.At present,China’s economy has entered the“New Normal”.In order to achieve“Sound and Rapid”economic development,it is imperative to transform the industrial structure.Using econometric analysis and based on China’s economic data from 1978 to 2020,this paper explores the different impacts of three industrial sectors on economic growth.Thus it analyzes the internal mechanism of China’s economic growth.It is concluded that the contribution of the tertiary industry to the national GDP is the largest,the level of secondary industry is medium,and the primary industry is the smallest.Finally,according to the calculation results,this paper puts forward corresponding suggestions for the optimization of China’s industrial structure,in order to achieve sound and rapid development of the national economy.
文摘The main aim of this paper is to present and emphasize the contribution of stochastic numerical methods as must tools for the modern econometric modelisation. Indeed, the stochastic numerical methods play an important role in mathematical modelling and the econometric analysis because they model uncertainties that govern the real-world data. However these powerful tools are not well-known and understood by many economists and financial econometricians.
文摘This article used the Cluster analysis of statistical method to separate China's 30 provinces and municipalities into three categories according to their energy consumption discrepancies and characteristics from 1985 to 2007. The categories were high, moderate and low energy consumption areas and they had significant differences in energy consumption. Based on this classification, the authors analyzed the influencing factors of energy consumption in the three areas by means of panel data econometric model. The results showed that the influencing factors were obviously different. In order to support national goal of energy conservation and emission reduction, the energy measures and policies should be distinctly taken.
基金Sponsored by Humanity and Social Science Youth Foundation of Ministry of Education of China(17YJCZH197)
文摘Room occupancy rate is a key indicator of star-rated hotel management quality. This paper takes Cobb-Douglas production function as the theoretical framework. Spatial Moran index of autocorrelation, Spatial Lag Model(SLM) and Spatial Error Model(SEM) are used to analyze the star-rated hotels labor productivity of 31 provincial regions in China's Mainland based on the star-rated hotels statistical data of year 2016. The spatial correlation and spatial difference of the star-rated hotels labor productivity is discussed. This paper studies the impact of three factors on spatial characteristics of star-rated hotels labor productivity in China's Mainland. The econometric estimation results show that:(1) Star-rated hotels labor productivity present significant spatial dependence and spatial difference in China's Mainland.(2) The estimation results of Ordinary least Squares(OLS) are reliable.(3) The reliability of the results obtained by the Spatial Error Model(SEM) analysis is the highest, and has a stronger explanatory power to the spatial relationship of star-rated hotels labor productivity in China's Mainland. The average room occupancy rate has more influence on the labor productivity of the provincial star-rated hotels than the impact of capital and labor.
文摘With the intensified competition in the capital market,the continuous development of internet finance,and the gradual loosening of market regulation,the profit pressure on securities firms relying on traditional business is increasing.In order to seek new profit growth points,many securities firms have ventured into business diversification,but with varying results.From the perspective of enterprise operational sustainability,econometric methods are used to explore the relationship between the diversification and business performance of securities firms in China,putting forward diversification strategies suitable for these firms.
基金The National Social Science Foundation of China(23BJL091)。
文摘This study measured the level of innovation achievement protection and the degree of internal structural upgrading of the productive service industry in 28 provinces of China from 2000 to 2022.Exploratory spatial analysis methods were used to test the spatial correlation between the two variables,and the spatial impact of innovation achievement protection on the optimization of the internal structure of the productive service industry was examined at the national and sectoral levels.The results showed three main aspects of this system.(1)The agglomeration level of innovation achievement protection and internal structure optimization of the productive service industry between regions in China continued to increase during the sample period,and there was a clear similarity and synchronicity in the spatial evolution of the two variables.(2)The overall improvement in the protection level of innovative achievements is conducive to promoting the internal structural upgrading of China’s productive service industry.However,there are significant differences in the degree to which the protection of innovative achievements affects the internal structural upgrading of the productive service industry in the four major regions of the East,Central,Northeast,and West.The protection of innovative achievements in the East and Central regions significantly promotes the internal structural optimization of the productive service industry,while this effect is not significant in the western and northeastern regions.(3)The results of the robustness test indicate that the impact of internal structural upgrading of the productive service industry in the previous year on the level of innovation achievement protection is not significant.The interference from abnormal values of the internal structural upgrading of the productive service industry in various regions and the influence of municipalities directly under the central government on the regression results are not significant.After replacing the main variable,the coefficient of the innovation achievement protection level remained significantly positive.The conclusions of this study supplement and improve the theory of innovation achievement protection and industrial transformation and upgrading,providing decision-making support for improving the level of innovation achievement protection and promoting the internal structural upgrading of the productive service industries in China.
文摘Urban agglomeration plays a vital role in fostering high-quality and sustainable development in China,where urbanization rates signifi-cantly influence both urban and rural environments,generating different economic and socio-spatial impacts that,in turn,influence carbon emissions in cities.To delve into the influencing mechanisms of carbon emissions,this paper examines the spatio-temporal pattern of carbon emissions across 41 cities in the Yangtze River Delta urban agglomeration in China.It utilizes data on economic,social,and spatial factors from 2012 to 2019 and employs a spatial econometric regression model for analysis.The results indicate that carbon emissions of cities in the urban agglomeration exhibited strong spatial correlation from 2012 to 2019,characterized by relatively stable cold and hot spots,along with continuous outward spread of high-value zones.Economic and social factors demonstrate a significant positive spatial correlation with carbon emissions of a city,with weak spatial spillover effects.Spatial factors exhibit correlations with carbon emissions in both the city and neighboring cities,with strong spatial spillover effects.Moreover,the spatial layout and functional division of cities in the urban agglomeration also significantly impact the spatio-temporal pattern of carbon emissions.
基金supported by the National Natural Science Foundation of China under Grant No.71373065
文摘In order to explore the factors and their complex mechanism affecting the price dynamics under the clean development mechanism (CDM), this article employs the secondary Certified Emission Reduction (sCER) carbon price as the study object, and analyzes its influencing factors from aspects of the international carbon-reduction policies, macroeconomic fluctuations, energy and similar carbon products prices. The innovation of this paper lies in: Introducing necessary factor (the developing countries pricing power) and the application of several international representative indicators to un- derline the "world" nature of CDM; utilizing different econometric models to obtain noteworthy and more robust results. The authors test the theoretical findings with multiple stationary time series from the launch of CDM to present (2008-2016). The results reveal that sCER price fluctuation shows the characteristic of asymmetry and substantial persistence. There is a strong statistically significant relationship between macroeconomic conditions, coal and oil prices, with the price of sCER. The authors discover that the pricing power of developing countries indeed has a clear but small impact on the sCER price changes, whereas the price elasticity of supply under CDM is so weak. The interaction between EU emission allowances (EUAs) and sCER presents a shift from dependency to substitution.
基金National Natural Science Foundation of China,No.42101318National Key Research and Development Program of China,No.2018YFD1100101Science and Technology Service Network Initiative of Chinese Academy of Sciences,No.KFJ-STS-ZDTP-011。
文摘Rural decline has become a global problem.To address this issue,the division of rural functions and identification of driving factors are important means of rural revitalization.Taking the town area as a unit,this study conducts a division and evolution analysis of rural regional functions in Jiangsu province in coastal China by constructing an evaluation system using the spatial econometric model to diagnose endogenous and exogenous driving factors of rural multifunction formation.The results show that the functions of agricultural supply and ecological conservation have decreased,while the functions of economic development and social security have increased.Agricultural production functions are concentrated in northern and central Jiangsu.The economic development function is mainly based on industrial development,and is the strongest in southern Jiangsu.Social security functions are concentrated in suburban area,county centers,and key towns.High-value areas of ecological conservation are concentrated along lakes,the coast,and hilly areas of southern Jiangsu.The multifunctional development of villages and towns is affected by endogenous and exogenous factors,including economic geographic location,natural resources,economic foundation,human capital,traffic conditions,market demand,infrastructure,and environmental governance.Natural factors have a significant impact on the supply of agricultural products and the formation of ecological conservation functions.The effects of socioeconomic factors on these four functions differ significantly.This study expands the theory of rural development functions,the classification and zoning paradigm,and the quantitative study of driving mechanisms.The results provide a reference for practical value and policy significance for the reconstruction of rural functions and rural revitalization.
基金National Natural Science Foundation of China,No.41771157National Key Research and Development Program of China,No.2018YFB0505402+1 种基金Scientific Research Project of Beijing Education Committee,No.KM201810028014Capacity Building for Sci-Tech Innovation-Fundamental Scientific Research Funds,No.025185305000/192
文摘Village is an important implementation unit of national poverty alleviation and development strategies of rural China, and identifying the poverty degree, poverty type and poverty contributing factors of each poverty-stricken village is the precondition and guarantee of taking targeted measures in poverty alleviation strategies of China. To respond it, we construct a village-level multidimensional poverty measuring model, and use indicator contribution degree indices and linear regression method to explore poverty factors, while adopting Least Square Error(LSE) model and spatial econometric analysis model to identify the villages' poverty types and poverty difference. The case study shows that:(1) Spatially, there is obvious territoriality in the distribution of poverty-stricken villages, and the poverty-stricken villages are concentrated in contiguous poverty-stricken areas. The areas with the highest VPI, in a descending order, are Gansu, Yunnan, Guizhou, Guangxi, Hunan, Qinghai, Sichuan, and Xinjiang.(2) The main factors contributing to the poverty of poverty-stricken villages in rural China include road construction, terrain type, frequency of natural disasters, per capita net income, labor force ratio, and cultural quality of labor force. The main causes of poverty include underdeveloped road construction conditions, frequent natural disasters, low level of income, and labor conditions.(3) Chinese poverty-stricken villages include six main subtypes, and most poverty-stricken villages are affected by multiple poverty-forming factors, reflected by a relatively high proportion of the three-factor dominant type, four-factor coordinative type, and five-factor combinative type.(4) There exist significant poverty differences in terms of geographical location and policy support, and the governments still need to carry out targeted poverty alleviation measures according to local conditions. The research can not only draw a macro overall poverty-reduction outline of impoverished villages in China, but also depict the specific poverty characteristics of each village, helping the government departments of pov-erty alleviation at all levels to mobilize all kinds of anti-poverty resources.
文摘Over the last decade, India has started to concentrate earnestly on renewable energy. The Indian government, as well as different state governments, are adopting policy instruments such as feed in tariff, captive consumption, renewable purchase obligation and genera- tion based incentive etc. aimed at renewable energy development. This paper evaluates the effectiveness of state level incentives for the development of wind energy in India. Fixed effect panel data modelling technique of econometric analysis is used to analyse the data of 26 Indian states in 11 years. The results show that feed in tariff and captive consumption are the significant predictors of wind energy development. However, renewable purchase obligation does not affect wind energy significantly.