This study explores the application of Bayesian econometrics in policy evaluation through theoretical analysis. The research first reviews the theoretical foundations of Bayesian methods, including the concepts of Bay...This study explores the application of Bayesian econometrics in policy evaluation through theoretical analysis. The research first reviews the theoretical foundations of Bayesian methods, including the concepts of Bayesian inference, prior distributions, and posterior distributions. Through systematic analysis, the study constructs a theoretical framework for applying Bayesian methods in policy evaluation. The research finds that Bayesian methods have multiple theoretical advantages in policy evaluation: Based on parameter uncertainty theory, Bayesian methods can better handle uncertainty in model parameters and provide more comprehensive estimates of policy effects;from the perspective of model selection theory, Bayesian model averaging can reduce model selection bias and enhance the robustness of evaluation results;according to causal inference theory, Bayesian causal inference methods provide new approaches for evaluating policy causal effects. The study also points out the complexities of applying Bayesian methods in policy evaluation, such as the selection of prior information and computational complexity. To address these complexities, the study proposes hybrid methods combining frequentist approaches and suggestions for developing computationally efficient algorithms. The research also discusses theoretical comparisons between Bayesian methods and other policy evaluation techniques, providing directions for future research.展开更多
This paper utilizes a panel data of 31 provinces in China spanning from 2007 to 2014.Spatial econometrics is applied to carry out regression analysis of the impact of urbanization and factor inputs on China's econ...This paper utilizes a panel data of 31 provinces in China spanning from 2007 to 2014.Spatial econometrics is applied to carry out regression analysis of the impact of urbanization and factor inputs on China's economic growth.By comparing differences among regions,this paper finds that in the regional level,the positive effect of urbanization in the Eastern region and the Western region is significant,and the positive effect of the proportion of input factors in the Central region is also significant but to a lesser extent.In general,there exists spatial spill-over effect between urbanization and factor inputs structure and economic growth,i.e.,both are capable of producing positive effect,but the input role played by the scale factor has diminishing marginal effect.Urbanization is more likely to become the driving force of economic growth and to stimulate economic growth.展开更多
Due to the outbreak of the Covid-19 in 2020,online education has become the mainstream.After the epidemic,the blending learning mode has also become a key goal of the teaching reform of colleges and universities,and t...Due to the outbreak of the Covid-19 in 2020,online education has become the mainstream.After the epidemic,the blending learning mode has also become a key goal of the teaching reform of colleges and universities,and the blending learning mode of various courses has blossomed everywhere.In this context,this paper used the Econometrics course as the carrier,analyzed the many unreasonable problems in the traditional Econometrics course,and proposed an optimization plan and path for the blending learning mode to address these problems.展开更多
Regression is a widely used econometric tool in research. In observational studies, based on a number of assumptions, regression-based statistical control methods attempt to analyze the causation between treatment and...Regression is a widely used econometric tool in research. In observational studies, based on a number of assumptions, regression-based statistical control methods attempt to analyze the causation between treatment and outcome by adding control variables. However, this approach may not produce reliable estimates of causal effects. In addition to the shortcomings of the method, this lack of confidence is mainly related to ambiguous formulations in econometrics, such as the definition of selection bias, selection of core control variables, and method of testing for robustness. Within the framework of the causal models, we clarify the assumption of causal inference using regression-based statistical controls, as described in econometrics, and discuss how to select core control variables to satisfy this assumption and conduct robustness tests for regression estimates.展开更多
This paper summarizes my previous work in Lin (2010), in which I use spatial econometrics to analyze air pollution externalities. In Lin (2010), state-by-state source-receptor transfer coefficients that can be used as...This paper summarizes my previous work in Lin (2010), in which I use spatial econometrics to analyze air pollution externalities. In Lin (2010), state-by-state source-receptor transfer coefficients that can be used as a basis for a location- differentiated permit system are estimated. Results affirm the importance of regional transport in determining local ozone air quality, although owing to non-monotonicities in ozone production the externality is not always negative. Because the origin of emissions matters, results also reject a non-spatially differentiated NOx cap and trade program as an appropriate mechanism for reducing ozone smog.展开更多
This is a critical note regarding the currently established econometrics of time series. The criticism involves commonly practiced mechanistic modeling and testing of relationships, taking econometrics away from econo...This is a critical note regarding the currently established econometrics of time series. The criticism involves commonly practiced mechanistic modeling and testing of relationships, taking econometrics away from economics. Among others, modeling economic trends as simple functions of time is extremely naive and testing for cointegration lacks a proper economic foundation.展开更多
Researchers must understand that naively relying on the reliability of statistical software packages may result in suboptimal, biased, or erroneous results, which affects applied economic theory and the conclusions an...Researchers must understand that naively relying on the reliability of statistical software packages may result in suboptimal, biased, or erroneous results, which affects applied economic theory and the conclusions and policy recommendations drawn from it. To create confidence in a result, several software packages should be applied to the same estimation problem. This study examines the results of three software packages (EViews, R, and Stata) in the analysis of time-series econometric data. The time-series data analysis which presents the determinants of macroeconomic growth of Sri Lanka from 1978 to 2020 has been used. The study focuses on testing for stationarity, cointegration, and significant relationships among the variables. The Augmented Dickey-Fuller and Phillips Perron tests were employed in this study to test for stationarity, while the Johansen cointegration test was utilized to test for cointegration. The study employs the vector error correction model to assess the short-run and long-term dynamics of the variables in an attempt to determine the relationship between them. Finally, the Granger Causality test is employed in order to examine the linear causation between the concerned variables. The study revealed that the results produced by three software packages for the same dataset and the same lag order vary significantly. This implies that time series econometrics results are sensitive to the software that is used by the researchers while providing different policy implications even for the same dataset. The present study highlights the necessity of further analysis to investigate the impact of software packages in time series analysis of economic scenarios.展开更多
To capitalize on the synergies between the Econometrics course and the Environmental Economics major,this paper aims to enhance students’ability to conduct empirical analysis and practical application using econometr...To capitalize on the synergies between the Econometrics course and the Environmental Economics major,this paper aims to enhance students’ability to conduct empirical analysis and practical application using econometric models.It also seeks to promote collaborative teaching through case studies and model research.The primary focus is on the hot research issues within the field of environmental economics,utilizing the econometric model as a vehicle for instruction.To achieve this,the paper proposes the development of a comprehensive case library specific to environmental economics.This resource will serve to optimize the case teaching approach,incorporating the use of econometric software,and fostering interactive teaching models between educators and students.By implementing these strategies,the paper outlines a path and mode for collaborative teaching that effectively bridges the gap between econometrics and environmental economics.展开更多
This study investigates the spatial courting between digital economic signs and local monetary overall performance throughout ten provinces in Sumatra,Indonesia,from 2019 to 2022.As digitalization hastens economic and...This study investigates the spatial courting between digital economic signs and local monetary overall performance throughout ten provinces in Sumatra,Indonesia,from 2019 to 2022.As digitalization hastens economic and business sports,devices together with fintech lending,e-cash,debit card usage,and e-commerce are increasingly more diagnosed as capability drivers of regional increase.But,the unequal distribution of digital infrastructure and monetary literacy across regions raises issues approximately the inclusivity of these benefits.constructing upon current findings by using Miranti et al.(2024),this research employs spatial econometric fashions-particularly the Spatial Lag model(SLM)and Spatial mistakes model(SEM)-to evaluate how digital variables influence provincial financial overall performance while accounting for spatial spillover consequences.The results reveal that fintech lending and debit card usage exert a positive and significant impact on economic growth,whereas the effect of e-money is negative,suggesting potential substitution effects or access constraints.Spatial dependency is also evident,as demonstrated by the significant lambda coefficient in the SEM model.These findings highlight the importance of spatially coordinated digital policies,particularly in addressing disparities and enhancing digital financial inclusion.The study concludes with policy recommendations aimed at fostering inclusive and spatially balanced digital economic development in Sumatra.展开更多
The rapid development of technology has led to an ever-increasing demand for electrical energy.In the context of Timor-Leste,which still relies on fossil energy sources with high operational costs and significant envi...The rapid development of technology has led to an ever-increasing demand for electrical energy.In the context of Timor-Leste,which still relies on fossil energy sources with high operational costs and significant environmental impacts,electricity load forecasting is a strategic measure to support the energy transition towards the Net Zero Emission(NZE)target by 2050.This study aims to utilize historical electricity load data for the period 2013–2024,as well as data on external factors affecting electricity consumption,to forecast electricity load in Timor-Leste in the next 10 years(2025–2035).The forecasting results are expected to support efforts in energy distribution efficiency,reduce operational costs,and inform decisions related to the sustainable energy transition.The method used in this study consists of two main approaches:the causality method,represented by the econometric Principal Component Analysis(PCA)model,which involves external factors in the data processing process,and the time series method,utilizing the LSTM,XGBoost,and hybrid(LSTM+XGBoost)models.In the time series method,data processing is combined with two approaches:the sliding window and the rolling recursive forecast.The performance of each model is evaluated using the Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and Mean Absolute Percentage Error(MAPE).The model with the lowest MAPE(<10%)is considered the best-performing model,indicating the highest accuracy.Additionally,a Monte Carlo simulation with 50,000 iterations was used to process the data and measure the prediction uncertainty,as well as test the calibration of the electricity load projection data.The results showed that the hybrid model(LSTM+XGBoost)with a rolling forecast recursive approach is the best-performing model in predicting electricity load in Timor-Leste.This model yields an RMSE of 75.76 MW,an MAE of 55.76 MW,and an MAPE of 5.27%,indicating a high level of accuracy.In addition,the model is also indicated as one that fits the characteristics of electricity load in Timor-Leste,as it produces the lowest percentage of forecasting error in predicting electricity load.The integration of the best model with Monte Carlo Simulation,which yields a p-value of 0.565,suggests that the results of electricity load projections for the period 2025–2035 are well-calibrated,reliable,accurate,and unbiased.展开更多
In this research work,the problems of connection between various harmful substances emitted into the atmosphere and population morbidity indicators were analyzed in the Navoi region,located in the industrialized and a...In this research work,the problems of connection between various harmful substances emitted into the atmosphere and population morbidity indicators were analyzed in the Navoi region,located in the industrialized and arid climate region of the Republic of Uzbekistan,in the Central Asian region.In today’s globalization process,due to the rapid development of the industry,several problems related to the health of the population are also appearing,so it is more important than ever to pay serious attention to solving these problems.Item 11 of the UN Sustainable Development Goals is also dedicated to the sustainable development of cities,and it is especially emphasized that the people living in the cities of the Asian continent have a very low chance of breathing clean air.Issues such as a very thorough analysis of this situation,improving the environmental situation as much as possible,transitioning to a green economy as soon as possible,and strengthening the health of the population are more important.In the implementation of this study,using methods such as statistical data analysis,sociological survey,and econometric modeling with the help of R Studio software,an attempt was made to determine the correlation between various harmful substances released into the atmosphere and disease groups of the population.This study’s conclusions show a direct relationship between the harmful substances released into the atmosphere and some types of population diseases in the industrialized region of Uzbekistan in Navoi,and their reduction by 2028 forecasts is presented.Decision-making organizations can use these results to prevent this situation from exacerbating.展开更多
Green technology innovation has gradually become an important driving force to promote new quality productivity.This paper constructs a quantitative index system of new quality productivity based on the three major el...Green technology innovation has gradually become an important driving force to promote new quality productivity.This paper constructs a quantitative index system of new quality productivity based on the three major elements of workers,labour objects and labour tools,and empirically analyses the impact of green technology innovation on the level of new quality productivity using spatial econometric model and VAR model.The result shows that:(1)The level of new quality productivity is not only affected by its own factors,but also by the significant spatial spillover effect between regions,especially in the case of strong geographic proximity,the interregional economic activities and resource allocation have a strong interaction and dependence.(2)The direct effect of green technology innovation is negative,mainly due to the high R&D investment and the short-term cost increase brought about by technological transformation,but its indirect effect is positive,showing that green technology has a positive effect on the new quality productivity enhancement of neighbouring regions through technology diffusion and cooperative innovation.(3)The eastern and western regions are affected by high upfront costs and transformation challenges,showing negative effects;while the central and northeastern regions benefit from policy support and industrial upgrading,showing positive effects.(4)Impulse response function analysis shows that the short-term impact of green technological innovation on new quality productivity is negative,but the long-term potential is significant,and the negative effect gradually diminishes over time.Based on this,this paper puts forward the suggestions of optimising the green innovation input structure,formulating regional differentiated policies and strengthening regional synergistic cooperation,which provide the theoretical basis and practical path for realising the green transformation and high-quality development of the economy.展开更多
As the goal of"low carbon"sustainable development becomes more salient,the corporations'environmental,social,and governance(ESG)practices are under higher visibility.How to promote the ESG performance of...As the goal of"low carbon"sustainable development becomes more salient,the corporations'environmental,social,and governance(ESG)practices are under higher visibility.How to promote the ESG performance of corporations has become a big challenge that needs to be solved.Spatial econometrics methods based on panel data on listed corporations in the period from 2018 to 2023 are used in the paper to empirically analyze the peer effect of a corporation from the view of strategic interaction.The results found relatively positive industry peer effects as well as regional peer effects.However,the latter is much weaker.Industry-wise results indicate that most sectors demonstrate positive peer competition on ESG issues,with only a few,like the special equipment manufacturing industry,not showing significant peer effects.The empirical results in this paper support the mode of cooperative interaction among firms,help broaden the scope of understanding factors that encourage ESG practices,and suggest relevant policies for boosting corporate social responsibilities and sustainable development through encouraging factors.展开更多
Green innovation is an important driving force for high-quality development and an important guarantee for the revitalization of the old industrial base in Northeast China.However,research on green innovation is still...Green innovation is an important driving force for high-quality development and an important guarantee for the revitalization of the old industrial base in Northeast China.However,research on green innovation is still insufficient.Using the super-efficiency epsilon-based measure Malmquist model,kernel density estimation,and spatial econometric model,this study investigated the spatiotemporal evolution characteristics and influencing factors of green innovation efficiency(GIE)in Northeast China from 2005 to 2020.The results reveal that:1)The GIE in Northeast China has obvious phased characteristics,where 2005-2011 was a period of fluctuating decline while 2012-2020 was a period of fluctuating increase,reflecting the severe resource and environmental constraints faced by the green innovation process.2)The GIE in the Northeast China has a significant spatial dependence,which has not formed a relatively stable spatial club feature.The process for improving the GIE in the Northeast China in the future is still arduous and far off.3)The interweaving and mutual influence of nonequilibrium factors have led to the diversity and complexity of the spatiotemporal pattern evolution of GIE.Overall,the level of economic development and industrial structure has a positive effect,while foreign investment and industrial agglomeration have a negative effect.The direct effects of government regulation,resource endowment,science and technology,environmental regulation,and urbanization are not significant.The research conclusion of this article can provide important reference for the revitalization of Northeast China.展开更多
Econometric simultaneous equation models play an important role in making economic policies, analyzing economic structure and economic forecasting. This paper presents local linear estimators by TSLS with variable ban...Econometric simultaneous equation models play an important role in making economic policies, analyzing economic structure and economic forecasting. This paper presents local linear estimators by TSLS with variable bandwidth for every structural equation in semi-parametric simultaneous equation models in econometrics. The properties under large sample size were studied by using the asymptotic theory when all variables were random. The results show that the estimators of the parameters have consistency and asymptotic normality, and their convergence rates are equal to n^-1/2. And the estimator of the nonparametric function has the consistency and asymptotic normality in interior points and its rate of convergence is equal to the optimal convergence rate of the nonparametric function estimation.展开更多
Using China’s regional input–output table,the paper constructs indicators of manufacturing servitization,matches manufacturing servitization at the regional level with city data,and uses spatial econometrics to empi...Using China’s regional input–output table,the paper constructs indicators of manufacturing servitization,matches manufacturing servitization at the regional level with city data,and uses spatial econometrics to empirically analyze the impact of manufacturing servitization on urban sulfur dioxide(SO_(2))emissions within the classical Environmental Kuznets Curve(EKC)framework.The results show that manufacturing servitization can reduce SO_(2) emissions.Producer servitization and consumptive services can both significantly reduce industrial SO_(2) emissions.Transportation and warehousing servitization,information servitization,leasing,and commercial servitization,technology research and development servitization significantly reduce SO_(2) emissions;technology research and development servitization,in particular,have the largest influence coefficient,while the reduction effect of servitization in the wholesale and retail and finance sectors is not significant.The study also found that servitization reduced the SO_(2) emissions through technological innovation and industrial structure upgrading.展开更多
In the context of building a country with a strong transportation network,railway container transportation(RCT)is an important means of reducing costs,increasing efficiency,and adjusting transportation structures.Thus...In the context of building a country with a strong transportation network,railway container transportation(RCT)is an important means of reducing costs,increasing efficiency,and adjusting transportation structures.Thus,its impact on regional economic development is important.Based on data from railway container-handling stations and spatial econometric models,this study discusses the differences in the development of RCT and their impact on regional economic development at different leves.This study has three main findings:first,there are significant regional differences in the development of the RCT.The intra-regional differences between the eastern and central regions of China(which do not include Hong Kong,Macao and Taiwan)are gradually narrowing,while the regional differences in the western region are widening.Meanwhile,the intra-regional differences in important economic zones such as Pearl River Delta Economic Zone(PRDEZ),Chengdu-Chongqing Economic Zone(CYEZ),Bohai Rim Economic Zone(BHEZ),and Yangtze River Delta Economic Zone(YRDEZ)are narrowing daily.Second,the development differences of RCT in regional level and important economic regions level show different trends.The unbalanced features of large regions are increasingly evident,whereas the differences in economic regions are decreasing.However,the problem of overlapping RCT remains prominent.Third,the transformation of RCT development mode and fierce competition among transportation modes cause RCT to have a restraining effect on the regional economy at three levels.Rational allocation of resources and other means must be used to guide the transformation from inhibition to promotion,and by formulating targeted policies that will promote the development of RCT,which will improve the transportation structure and help construct a country with a strong transportation system.展开更多
This study aims to reveal the spatial structural characteristics of 1,652 Ethnic-Minority Villages(EMV)in China and to analyze the mechanisms driving their spatial heterogeneity.EMV are a special type of settlement sp...This study aims to reveal the spatial structural characteristics of 1,652 Ethnic-Minority Villages(EMV)in China and to analyze the mechanisms driving their spatial heterogeneity.EMV are a special type of settlement space that preserve a large number of historical traces of the ethnic culture of ancient China.They are important carriers of China’s excellent traditional culture and are key to the implementation of rural revitalization strategies.In this study,1652 EMV in China were selected as the research subjects.The Nearest Neighbor Index,kernel density,and spatial autocorrelation index were employed to reveal the spatial structural characteristics of minority villages.Neural network models,spatial lag models,and geographical detectors were used to analyze the formation mechanism of spatial heterogeneity in EMV.The results indicate that:(1)EMV exhibit significant spatial differentiation characterized by“single-core with multiple surrounding sub-centers,”“polarization between east and west,”“decreasing quantity from southwest to east coast to northeast to northwest,”and“large dispersion with small agglomeration.”(2)EMV are mainly distributed in areas rich in intangible cultural heritage,with high vegetation coverage and low altitude,far from central cities,and having limited arable land and an underdeveloped economy and transportation,particularly in shaded or riverbank areas.(3)Distance from the nearest river(X3),distance from central cities(X8),national intangible cultural heritage(X9),and NDVI(X10)were the main driving factors affecting the spatial distribution of EMV,whereas elevation(X1)and GDP(X5)had the weakest influence.As EMV are a relatively unique territorial spatial unit,the identification of their spatial heterogeneity characteristics not only deepens the research content of settlement geography,but also involves the assessment,protection,and development of Minority Villages,which is of great significance for the inheritance and utilization of excellent ethnic cultures in the era.展开更多
文摘This study explores the application of Bayesian econometrics in policy evaluation through theoretical analysis. The research first reviews the theoretical foundations of Bayesian methods, including the concepts of Bayesian inference, prior distributions, and posterior distributions. Through systematic analysis, the study constructs a theoretical framework for applying Bayesian methods in policy evaluation. The research finds that Bayesian methods have multiple theoretical advantages in policy evaluation: Based on parameter uncertainty theory, Bayesian methods can better handle uncertainty in model parameters and provide more comprehensive estimates of policy effects;from the perspective of model selection theory, Bayesian model averaging can reduce model selection bias and enhance the robustness of evaluation results;according to causal inference theory, Bayesian causal inference methods provide new approaches for evaluating policy causal effects. The study also points out the complexities of applying Bayesian methods in policy evaluation, such as the selection of prior information and computational complexity. To address these complexities, the study proposes hybrid methods combining frequentist approaches and suggestions for developing computationally efficient algorithms. The research also discusses theoretical comparisons between Bayesian methods and other policy evaluation techniques, providing directions for future research.
文摘This paper utilizes a panel data of 31 provinces in China spanning from 2007 to 2014.Spatial econometrics is applied to carry out regression analysis of the impact of urbanization and factor inputs on China's economic growth.By comparing differences among regions,this paper finds that in the regional level,the positive effect of urbanization in the Eastern region and the Western region is significant,and the positive effect of the proportion of input factors in the Central region is also significant but to a lesser extent.In general,there exists spatial spill-over effect between urbanization and factor inputs structure and economic growth,i.e.,both are capable of producing positive effect,but the input role played by the scale factor has diminishing marginal effect.Urbanization is more likely to become the driving force of economic growth and to stimulate economic growth.
基金The 2019 Ministry of Education industry-university cooperation collaborative education project"Research on the Construction of Economics and Management Professional Data Analysis Laboratory"(Project number:201902077020).
文摘Due to the outbreak of the Covid-19 in 2020,online education has become the mainstream.After the epidemic,the blending learning mode has also become a key goal of the teaching reform of colleges and universities,and the blending learning mode of various courses has blossomed everywhere.In this context,this paper used the Econometrics course as the carrier,analyzed the many unreasonable problems in the traditional Econometrics course,and proposed an optimization plan and path for the blending learning mode to address these problems.
基金This research was funded by the National Natural Science Foundation of China(Grant No.72074060).
文摘Regression is a widely used econometric tool in research. In observational studies, based on a number of assumptions, regression-based statistical control methods attempt to analyze the causation between treatment and outcome by adding control variables. However, this approach may not produce reliable estimates of causal effects. In addition to the shortcomings of the method, this lack of confidence is mainly related to ambiguous formulations in econometrics, such as the definition of selection bias, selection of core control variables, and method of testing for robustness. Within the framework of the causal models, we clarify the assumption of causal inference using regression-based statistical controls, as described in econometrics, and discuss how to select core control variables to satisfy this assumption and conduct robustness tests for regression estimates.
文摘This paper summarizes my previous work in Lin (2010), in which I use spatial econometrics to analyze air pollution externalities. In Lin (2010), state-by-state source-receptor transfer coefficients that can be used as a basis for a location- differentiated permit system are estimated. Results affirm the importance of regional transport in determining local ozone air quality, although owing to non-monotonicities in ozone production the externality is not always negative. Because the origin of emissions matters, results also reject a non-spatially differentiated NOx cap and trade program as an appropriate mechanism for reducing ozone smog.
文摘This is a critical note regarding the currently established econometrics of time series. The criticism involves commonly practiced mechanistic modeling and testing of relationships, taking econometrics away from economics. Among others, modeling economic trends as simple functions of time is extremely naive and testing for cointegration lacks a proper economic foundation.
文摘Researchers must understand that naively relying on the reliability of statistical software packages may result in suboptimal, biased, or erroneous results, which affects applied economic theory and the conclusions and policy recommendations drawn from it. To create confidence in a result, several software packages should be applied to the same estimation problem. This study examines the results of three software packages (EViews, R, and Stata) in the analysis of time-series econometric data. The time-series data analysis which presents the determinants of macroeconomic growth of Sri Lanka from 1978 to 2020 has been used. The study focuses on testing for stationarity, cointegration, and significant relationships among the variables. The Augmented Dickey-Fuller and Phillips Perron tests were employed in this study to test for stationarity, while the Johansen cointegration test was utilized to test for cointegration. The study employs the vector error correction model to assess the short-run and long-term dynamics of the variables in an attempt to determine the relationship between them. Finally, the Granger Causality test is employed in order to examine the linear causation between the concerned variables. The study revealed that the results produced by three software packages for the same dataset and the same lag order vary significantly. This implies that time series econometrics results are sensitive to the software that is used by the researchers while providing different policy implications even for the same dataset. The present study highlights the necessity of further analysis to investigate the impact of software packages in time series analysis of economic scenarios.
基金supported by the Ministry of Education of Humanities and Social Science Project(21YJC630009)the National Natural Science Foundation of China(No.72104116).
文摘To capitalize on the synergies between the Econometrics course and the Environmental Economics major,this paper aims to enhance students’ability to conduct empirical analysis and practical application using econometric models.It also seeks to promote collaborative teaching through case studies and model research.The primary focus is on the hot research issues within the field of environmental economics,utilizing the econometric model as a vehicle for instruction.To achieve this,the paper proposes the development of a comprehensive case library specific to environmental economics.This resource will serve to optimize the case teaching approach,incorporating the use of econometric software,and fostering interactive teaching models between educators and students.By implementing these strategies,the paper outlines a path and mode for collaborative teaching that effectively bridges the gap between econometrics and environmental economics.
文摘This study investigates the spatial courting between digital economic signs and local monetary overall performance throughout ten provinces in Sumatra,Indonesia,from 2019 to 2022.As digitalization hastens economic and business sports,devices together with fintech lending,e-cash,debit card usage,and e-commerce are increasingly more diagnosed as capability drivers of regional increase.But,the unequal distribution of digital infrastructure and monetary literacy across regions raises issues approximately the inclusivity of these benefits.constructing upon current findings by using Miranti et al.(2024),this research employs spatial econometric fashions-particularly the Spatial Lag model(SLM)and Spatial mistakes model(SEM)-to evaluate how digital variables influence provincial financial overall performance while accounting for spatial spillover consequences.The results reveal that fintech lending and debit card usage exert a positive and significant impact on economic growth,whereas the effect of e-money is negative,suggesting potential substitution effects or access constraints.Spatial dependency is also evident,as demonstrated by the significant lambda coefficient in the SEM model.These findings highlight the importance of spatially coordinated digital policies,particularly in addressing disparities and enhancing digital financial inclusion.The study concludes with policy recommendations aimed at fostering inclusive and spatially balanced digital economic development in Sumatra.
文摘The rapid development of technology has led to an ever-increasing demand for electrical energy.In the context of Timor-Leste,which still relies on fossil energy sources with high operational costs and significant environmental impacts,electricity load forecasting is a strategic measure to support the energy transition towards the Net Zero Emission(NZE)target by 2050.This study aims to utilize historical electricity load data for the period 2013–2024,as well as data on external factors affecting electricity consumption,to forecast electricity load in Timor-Leste in the next 10 years(2025–2035).The forecasting results are expected to support efforts in energy distribution efficiency,reduce operational costs,and inform decisions related to the sustainable energy transition.The method used in this study consists of two main approaches:the causality method,represented by the econometric Principal Component Analysis(PCA)model,which involves external factors in the data processing process,and the time series method,utilizing the LSTM,XGBoost,and hybrid(LSTM+XGBoost)models.In the time series method,data processing is combined with two approaches:the sliding window and the rolling recursive forecast.The performance of each model is evaluated using the Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and Mean Absolute Percentage Error(MAPE).The model with the lowest MAPE(<10%)is considered the best-performing model,indicating the highest accuracy.Additionally,a Monte Carlo simulation with 50,000 iterations was used to process the data and measure the prediction uncertainty,as well as test the calibration of the electricity load projection data.The results showed that the hybrid model(LSTM+XGBoost)with a rolling forecast recursive approach is the best-performing model in predicting electricity load in Timor-Leste.This model yields an RMSE of 75.76 MW,an MAE of 55.76 MW,and an MAPE of 5.27%,indicating a high level of accuracy.In addition,the model is also indicated as one that fits the characteristics of electricity load in Timor-Leste,as it produces the lowest percentage of forecasting error in predicting electricity load.The integration of the best model with Monte Carlo Simulation,which yields a p-value of 0.565,suggests that the results of electricity load projections for the period 2025–2035 are well-calibrated,reliable,accurate,and unbiased.
文摘In this research work,the problems of connection between various harmful substances emitted into the atmosphere and population morbidity indicators were analyzed in the Navoi region,located in the industrialized and arid climate region of the Republic of Uzbekistan,in the Central Asian region.In today’s globalization process,due to the rapid development of the industry,several problems related to the health of the population are also appearing,so it is more important than ever to pay serious attention to solving these problems.Item 11 of the UN Sustainable Development Goals is also dedicated to the sustainable development of cities,and it is especially emphasized that the people living in the cities of the Asian continent have a very low chance of breathing clean air.Issues such as a very thorough analysis of this situation,improving the environmental situation as much as possible,transitioning to a green economy as soon as possible,and strengthening the health of the population are more important.In the implementation of this study,using methods such as statistical data analysis,sociological survey,and econometric modeling with the help of R Studio software,an attempt was made to determine the correlation between various harmful substances released into the atmosphere and disease groups of the population.This study’s conclusions show a direct relationship between the harmful substances released into the atmosphere and some types of population diseases in the industrialized region of Uzbekistan in Navoi,and their reduction by 2028 forecasts is presented.Decision-making organizations can use these results to prevent this situation from exacerbating.
基金supported by the project of Non-Tax Revenue of Yunnan Provincial Department of Finance(Grant No.FSYJ202119).
文摘Green technology innovation has gradually become an important driving force to promote new quality productivity.This paper constructs a quantitative index system of new quality productivity based on the three major elements of workers,labour objects and labour tools,and empirically analyses the impact of green technology innovation on the level of new quality productivity using spatial econometric model and VAR model.The result shows that:(1)The level of new quality productivity is not only affected by its own factors,but also by the significant spatial spillover effect between regions,especially in the case of strong geographic proximity,the interregional economic activities and resource allocation have a strong interaction and dependence.(2)The direct effect of green technology innovation is negative,mainly due to the high R&D investment and the short-term cost increase brought about by technological transformation,but its indirect effect is positive,showing that green technology has a positive effect on the new quality productivity enhancement of neighbouring regions through technology diffusion and cooperative innovation.(3)The eastern and western regions are affected by high upfront costs and transformation challenges,showing negative effects;while the central and northeastern regions benefit from policy support and industrial upgrading,showing positive effects.(4)Impulse response function analysis shows that the short-term impact of green technological innovation on new quality productivity is negative,but the long-term potential is significant,and the negative effect gradually diminishes over time.Based on this,this paper puts forward the suggestions of optimising the green innovation input structure,formulating regional differentiated policies and strengthening regional synergistic cooperation,which provide the theoretical basis and practical path for realising the green transformation and high-quality development of the economy.
基金supported by the National Natural Science Foundation of China(Grant No.72073045).
文摘As the goal of"low carbon"sustainable development becomes more salient,the corporations'environmental,social,and governance(ESG)practices are under higher visibility.How to promote the ESG performance of corporations has become a big challenge that needs to be solved.Spatial econometrics methods based on panel data on listed corporations in the period from 2018 to 2023 are used in the paper to empirically analyze the peer effect of a corporation from the view of strategic interaction.The results found relatively positive industry peer effects as well as regional peer effects.However,the latter is much weaker.Industry-wise results indicate that most sectors demonstrate positive peer competition on ESG issues,with only a few,like the special equipment manufacturing industry,not showing significant peer effects.The empirical results in this paper support the mode of cooperative interaction among firms,help broaden the scope of understanding factors that encourage ESG practices,and suggest relevant policies for boosting corporate social responsibilities and sustainable development through encouraging factors.
基金Under the auspices of the National Natural Science Foundation of China(No.42571228,42401212)National Natural Science Foundation of Shandong(No.ZR2024MD022)。
文摘Green innovation is an important driving force for high-quality development and an important guarantee for the revitalization of the old industrial base in Northeast China.However,research on green innovation is still insufficient.Using the super-efficiency epsilon-based measure Malmquist model,kernel density estimation,and spatial econometric model,this study investigated the spatiotemporal evolution characteristics and influencing factors of green innovation efficiency(GIE)in Northeast China from 2005 to 2020.The results reveal that:1)The GIE in Northeast China has obvious phased characteristics,where 2005-2011 was a period of fluctuating decline while 2012-2020 was a period of fluctuating increase,reflecting the severe resource and environmental constraints faced by the green innovation process.2)The GIE in the Northeast China has a significant spatial dependence,which has not formed a relatively stable spatial club feature.The process for improving the GIE in the Northeast China in the future is still arduous and far off.3)The interweaving and mutual influence of nonequilibrium factors have led to the diversity and complexity of the spatiotemporal pattern evolution of GIE.Overall,the level of economic development and industrial structure has a positive effect,while foreign investment and industrial agglomeration have a negative effect.The direct effects of government regulation,resource endowment,science and technology,environmental regulation,and urbanization are not significant.The research conclusion of this article can provide important reference for the revitalization of Northeast China.
基金This project is supported by National Natural Science Foundation of China （70371025）
文摘Econometric simultaneous equation models play an important role in making economic policies, analyzing economic structure and economic forecasting. This paper presents local linear estimators by TSLS with variable bandwidth for every structural equation in semi-parametric simultaneous equation models in econometrics. The properties under large sample size were studied by using the asymptotic theory when all variables were random. The results show that the estimators of the parameters have consistency and asymptotic normality, and their convergence rates are equal to n^-1/2. And the estimator of the nonparametric function has the consistency and asymptotic normality in interior points and its rate of convergence is equal to the optimal convergence rate of the nonparametric function estimation.
基金funded by the National Social Science Foundation of China[Grant No.23CGJ011 and Grant No.22BGJ029]National Natural Science Foundation of China[Grant No.72263015]Science and Technology Youth Project of the Jiangxi Provincial Department of Education[Grant No.GJJ200530].
文摘Using China’s regional input–output table,the paper constructs indicators of manufacturing servitization,matches manufacturing servitization at the regional level with city data,and uses spatial econometrics to empirically analyze the impact of manufacturing servitization on urban sulfur dioxide(SO_(2))emissions within the classical Environmental Kuznets Curve(EKC)framework.The results show that manufacturing servitization can reduce SO_(2) emissions.Producer servitization and consumptive services can both significantly reduce industrial SO_(2) emissions.Transportation and warehousing servitization,information servitization,leasing,and commercial servitization,technology research and development servitization significantly reduce SO_(2) emissions;technology research and development servitization,in particular,have the largest influence coefficient,while the reduction effect of servitization in the wholesale and retail and finance sectors is not significant.The study also found that servitization reduced the SO_(2) emissions through technological innovation and industrial structure upgrading.
基金Under the auspices of National Key Research and Development Program of China(No.2023YFB4302200)National Natural Science Foundation of China(No.71831002,72174053)+1 种基金Liaoning Province Xingliao Talent Plan(No.XLYC2008030)Talent Planning in Dalian(No.2022RG05)。
文摘In the context of building a country with a strong transportation network,railway container transportation(RCT)is an important means of reducing costs,increasing efficiency,and adjusting transportation structures.Thus,its impact on regional economic development is important.Based on data from railway container-handling stations and spatial econometric models,this study discusses the differences in the development of RCT and their impact on regional economic development at different leves.This study has three main findings:first,there are significant regional differences in the development of the RCT.The intra-regional differences between the eastern and central regions of China(which do not include Hong Kong,Macao and Taiwan)are gradually narrowing,while the regional differences in the western region are widening.Meanwhile,the intra-regional differences in important economic zones such as Pearl River Delta Economic Zone(PRDEZ),Chengdu-Chongqing Economic Zone(CYEZ),Bohai Rim Economic Zone(BHEZ),and Yangtze River Delta Economic Zone(YRDEZ)are narrowing daily.Second,the development differences of RCT in regional level and important economic regions level show different trends.The unbalanced features of large regions are increasingly evident,whereas the differences in economic regions are decreasing.However,the problem of overlapping RCT remains prominent.Third,the transformation of RCT development mode and fierce competition among transportation modes cause RCT to have a restraining effect on the regional economy at three levels.Rational allocation of resources and other means must be used to guide the transformation from inhibition to promotion,and by formulating targeted policies that will promote the development of RCT,which will improve the transportation structure and help construct a country with a strong transportation system.
文摘This study aims to reveal the spatial structural characteristics of 1,652 Ethnic-Minority Villages(EMV)in China and to analyze the mechanisms driving their spatial heterogeneity.EMV are a special type of settlement space that preserve a large number of historical traces of the ethnic culture of ancient China.They are important carriers of China’s excellent traditional culture and are key to the implementation of rural revitalization strategies.In this study,1652 EMV in China were selected as the research subjects.The Nearest Neighbor Index,kernel density,and spatial autocorrelation index were employed to reveal the spatial structural characteristics of minority villages.Neural network models,spatial lag models,and geographical detectors were used to analyze the formation mechanism of spatial heterogeneity in EMV.The results indicate that:(1)EMV exhibit significant spatial differentiation characterized by“single-core with multiple surrounding sub-centers,”“polarization between east and west,”“decreasing quantity from southwest to east coast to northeast to northwest,”and“large dispersion with small agglomeration.”(2)EMV are mainly distributed in areas rich in intangible cultural heritage,with high vegetation coverage and low altitude,far from central cities,and having limited arable land and an underdeveloped economy and transportation,particularly in shaded or riverbank areas.(3)Distance from the nearest river(X3),distance from central cities(X8),national intangible cultural heritage(X9),and NDVI(X10)were the main driving factors affecting the spatial distribution of EMV,whereas elevation(X1)and GDP(X5)had the weakest influence.As EMV are a relatively unique territorial spatial unit,the identification of their spatial heterogeneity characteristics not only deepens the research content of settlement geography,but also involves the assessment,protection,and development of Minority Villages,which is of great significance for the inheritance and utilization of excellent ethnic cultures in the era.
