In this paper,we propose STPLF,which stands for the short-term forecasting of locational marginal price components,including the forecasting of non-conforming hourly net loads.The volatility of transmission-level hour...In this paper,we propose STPLF,which stands for the short-term forecasting of locational marginal price components,including the forecasting of non-conforming hourly net loads.The volatility of transmission-level hourly locational marginal prices(LMPs)is caused by several factors,including weather data,hourly gas prices,historical hourly loads,and market prices.In addition,variations of non-conforming net loads,which are affected by behind-the-meter distributed energy resources(DERs)and retail customer loads,could have a major impact on the volatility of hourly LMPs,as bulk grid operators have limited visibility of such retail-level resources.We propose a fusion forecasting model for the STPLF,which uses machine learning and deep learning methods to forecast non-conforming loads and respective hourly prices.Additionally,data preprocessing and feature extraction are used to increase the accuracy of the STPLF.The proposed STPLF model also includes a post-processing stage for calculating the probability of hourly LMP spikes.We use a practical set of data to analyze the STPLF results and validate the proposed probabilistic method for calculating the LMP spikes.展开更多
We often hear statements like“the market raises expectations for central bank interest rate cuts,resulting in higher commodity prices”.Given the current situation,the People’s Bank of China might adopt a more accom...We often hear statements like“the market raises expectations for central bank interest rate cuts,resulting in higher commodity prices”.Given the current situation,the People’s Bank of China might adopt a more accommodative monetary policy to mitigate the impact of the China-U.S.trade friction.Will this further easing of the monetary environment lead to an increase in natural gas prices?展开更多
Stock price prediction is a typical complex time series prediction problem characterized by dynamics,nonlinearity,and complexity.This paper introduces a generative adversarial network model that incorporates an attent...Stock price prediction is a typical complex time series prediction problem characterized by dynamics,nonlinearity,and complexity.This paper introduces a generative adversarial network model that incorporates an attention mechanism(GAN-LSTM-Attention)to improve the accuracy of stock price prediction.Firstly,the generator of this model combines the Long and Short-Term Memory Network(LSTM),the Attention Mechanism and,the Fully-Connected Layer,focusing on generating the predicted stock price.The discriminator combines the Convolutional Neural Network(CNN)and the Fully-Connected Layer to discriminate between real stock prices and generated stock prices.Secondly,to evaluate the practical application ability and generalization ability of the GAN-LSTM-Attention model,four representative stocks in the United States of America(USA)stock market,namely,Standard&Poor’s 500 Index stock,Apple Incorporatedstock,AdvancedMicroDevices Incorporatedstock,and Google Incorporated stock were selected for prediction experiments,and the prediction performance was comprehensively evaluated by using the three evaluation metrics,namely,mean absolute error(MAE),root mean square error(RMSE),and coefficient of determination(R2).Finally,the specific effects of the attention mechanism,convolutional layer,and fully-connected layer on the prediction performance of the model are systematically analyzed through ablation study.The results of experiment show that the GAN-LSTM-Attention model exhibits excellent performance and robustness in stock price prediction.展开更多
Global climate change has created substantial difficulties in the areas of sustainability,development,and environmental conservation due to the widespread dependence on fossil fuels for energy production.Nevertheless,...Global climate change has created substantial difficulties in the areas of sustainability,development,and environmental conservation due to the widespread dependence on fossil fuels for energy production.Nevertheless,the promotion of renewable energy programs has the potential to significantly expedite endeavors aimed at tackling climate change.Thus,it is essential to conduct a thorough analysis that considers the financial aspects to fully understand the main hurdles that are preventing the advancement of renewable energy initiatives.Italy is a leading country in the worldwide deployment of renewable energy.The objective of this research is to assess the impact of financial growth,economic progress,and energy expenses on Italy’s adoption of renewable energy sources.By employing the Auto-Regressive Distributed Lag(ARDL)technique,we analyzed annual data spanning from1990 to 2022.Findings revealed that a 1%increase in financial and economic development would boost renewable energy consumption in the long run by 0.29%and 0.48%,respectively.Instead,a 1%increase in energy prices might reduce consumption of renewable energy by 0.05%in the long run.This study’s primary significance lies in furnishing actionable strategies for Italy to augment green finance for renewable energy,fostering sustained social and economic progress.Moreover,the analytical insights gleaned from this research offer valuable insights for energy-importing nations worldwide.展开更多
On April 2,the United States announced the implementation of the so-called“reciprocal tariffs”plan.Combined with factors such as the OPEC+plan to increase production starting in May,this led to a continuous plunge i...On April 2,the United States announced the implementation of the so-called“reciprocal tariffs”plan.Combined with factors such as the OPEC+plan to increase production starting in May,this led to a continuous plunge in the benchmark oil prices of WTI and Brent over the subsequent three trading days.Despite the significant impact of the United States’“reciprocal tariffs”plan on the global political and economic landscape,the fundamental dynamics of supply and demand remain the decisive factors in the fluctuations of international oil prices.The current trend of international oil price fluctuations is still primarily driven by the supply side,with both supply and demand factors playing a role.Investment,costs,and resource constraints on the supply side do not allow for a significant increase in crude oil production,while“consumption rigidity”on the demand side does not permit a significant decrease in crude oil demand.As a result,International oil prices are expected to fluctuate in the short term,but a significant decline is unlikely to be sustained in the near to medium term.In this context,Chinese oil companies should focus on four key areas to ensure the security of national oil and gas supplies:first,promoting high-quality increases in domestic oil and gas reserves and production;second,steadily strengthening the acquisition of overseas oil and gas resources;third,continuously driving innovation in oil and gas exploration and development technologies;fourth,enhancing the capacity for domestic oil and gas reserves in an orderly manner.展开更多
This paper investigates China's coal price volatility spreaders(CPVSs)from the supply side to locate the volatility source since coal price volatility may destabilize many downstream products'prices or even br...This paper investigates China's coal price volatility spreaders(CPVSs)from the supply side to locate the volatility source since coal price volatility may destabilize many downstream products'prices or even bring uncertainties to macroeconomic output.Especially in the carbon neutrality context,China's coal market is being reconstructed and responding to imbalances between supply and demand;identifying the CPVSs helps alleviate rising market instability and prevent energy-induced system risk.To achieve this objective,we explore causalities among 938 weekly coal prices reported by different coal-producing areas of China from 2006.9.4 to 2021.7.12 using the transfer entropy method.Then,coal price volatility influence is quantified to identify the CPVSs by conjointly using complex network theory and a rank aggregation method.The validity test demonstrates that the proposed hybrid method efficiently identifies the CPVSs as it correlates to many price determinants,e.g.,electricity and coal consumption and generation.The empirical results show that causalities among coal prices changed dramatically in 2016,2018,and 2020,affected by coal decapacity and carbon neutrality policies.Before 2018,coal-producing provinces with strong demand for coal and electricity,e.g.,Jiangxi,Chongqing,and Sichuan,were CPVSs;after 2019,those with comparative advantages in coal supply,e.g.,Gansu and Ningxia,were CPVSs.Overall,the coal market is unstable and sensitive to energy policy and external shocks.Policymakers and market participants are recommended to monitor and manage the CPVSs to improve energy security,avoid policy-induced instability and prevent risks caused by coal price fluctuations.展开更多
Between 2016 and 2024,the Chinese government incorporated several innovative drugs into the National Reimbursement Drug List(NRDL)through price negotiations.These negotiations led to significant price reductions,which...Between 2016 and 2024,the Chinese government incorporated several innovative drugs into the National Reimbursement Drug List(NRDL)through price negotiations.These negotiations led to significant price reductions,which in turn stimulated an increase in sales.This study aimed to assess the impact of this policy on the pricing,utilization,and overall expenditure of targeted lung cancer therapies included in the NRDL.Using an interrupted time series analysis of procurement data from 698 healthcare institutions,the study evaluated both immediate and long-term effects.In terms of immediate effects,price negotiations resulted in a significant decline in the defined daily dose cost(DDDc)for all targeted therapies(P<0.05).Regarding long-term trends,a significant shift was observed only in the pricing trajectory of Gefitinib,Icotinib,and Ensartinib(P<0.05).In terms of immediate effects on drug utilization,all targeted medicines experienced a substantial increase in volume(P<0.05),except for Gefitinib and Icotinib.Over the long term,the usage of all targeted therapies exhibited a significant upward trend(P<0.05).With respect to expenditure,the immediate impact of NRDL inclusion resulted in a significant increase in spending on Afatinib,Crizotinib,Osimertinib,Alectinib,and Ensartinib(P<0.05).Over time,total spending on targeted medicines showed a significant increase(P<0.05),except for Erlotinib.Overall,NRDL price negotiations successfully reduced the economic burden on lung cancer patients,improving both accessibility and affordability of targeted therapies in China.展开更多
While the significant role of technological innovation in promoting renewable energy has been extensively explored in the literature,limited attention has been paid to the impact of energy patents,particularly clean e...While the significant role of technological innovation in promoting renewable energy has been extensively explored in the literature,limited attention has been paid to the impact of energy patents,particularly clean energy patents and fossil fuel patents.This study pioneers an investigation into the effects of energy patents and energy prices on renewable energy consumption.The study utilizes data from 2000Q1 to 2023Q4 and,due to the nonlinear nature of the series,applies wavelet quantile-based methods.Specifically,it introduces the wavelet quantile cointegration approach to evaluate cointegration across different quantiles and time horizons,along with the wavelet quantile-on-quantile regression method.The results confirm cointegration across different periods and quantiles,highlighting the significant relationships between energy patents,economic factors,and renewable energy consumption.Furthermore,we found that fossil energy patents negatively affect renewable energy consumption,while clean energy patents have a similar but weaker effect,especially in the short term.In addition,higher energy prices promote renewable energy adoption while economic growth positively influences renewable energy consumption,particularly in the short term.The study formulates specific policies based on these findings.展开更多
Based on the financial data and stock price information of Bengang Steel Plates Co.Ltd.from 2004 to 2023,this paper uses SPSS 26 software,combined with DuPont Analysis and Wall Score Method,to explore the correlation ...Based on the financial data and stock price information of Bengang Steel Plates Co.Ltd.from 2004 to 2023,this paper uses SPSS 26 software,combined with DuPont Analysis and Wall Score Method,to explore the correlation between stock price and nine key financial indicators selected from three dimensions:profitability,development capability,and operating capability,including fixed asset growth rate,price-to-book ratio(P/B ratio),and gross profit margin.Through correlation analysis,multiple regression analysis,and curve fitting,the study finds that:fixed asset growth rate,P/B ratio,and gross profit margin show a significant positive correlation with stock price;return on equity(ROE),operating income,and accounts receivable turnover days show a significant negative correlation with stock price;earnings per share(EPS)and net profit growth rate do not show a significant correlation with stock price.The research results indicate that the stock price of Bengang Steel Plates Co.Ltd.is greatly affected by its asset scale and market valuation,while some profitability indicators have not been effectively transmitted to the stock price.Finally,countermeasures and suggestions are put forward from the aspects of cost control,technological innovation,market expansion,and financial structure optimization,so as to provide references for corporate operation and investment decisions.展开更多
Fluctuations in real estate prices are closely linked to the macro-economy,exerting a profound influence on social investment and consumption levels.As a key source of funding for the real estate market,bank credit si...Fluctuations in real estate prices are closely linked to the macro-economy,exerting a profound influence on social investment and consumption levels.As a key source of funding for the real estate market,bank credit significantly affects housing price changes in major Chinese cities.This paper explores the transmission mechanisms and pathways of bank credit on real estate prices through theoretical analysis and empirical research.It constructs a panel regression model to empirically analyze the relationship between bank credit scale and housing prices in 35 large and medium-sized Chinese cities from 2012 to 2022,assess the impact of credit on housing price fluctuations,and compare differences between first-tier and second-tier cities.Based on these findings,the paper proposes suggestions for regulating housing prices by controlling credit scale,aiming to deepen the understanding of the relationship between bank credit and housing prices and support the stable development of China’s macro-economy and real estate market.展开更多
This study examines the dynamic interplay between the US Dollar Index(USDI)and gold prices(GP)to assess the sustainability of gold price trends.Employing a rolling window bootstrapping causality test methodology acros...This study examines the dynamic interplay between the US Dollar Index(USDI)and gold prices(GP)to assess the sustainability of gold price trends.Employing a rolling window bootstrapping causality test methodology across full and sub-samples,the findings of this study challenge the conventional assumption of a stable long-term inverse correlation between USDI and GP,thereby validating the hypothesis that their relationship is nonlinear and time-dependent.During periods of heightened geopolitical and economic volatility,both the US dollar and gold function as safe-haven assets,with USDI fluctuations exerting a positive influence on GP.Conversely,under stable market conditions,the US dollar serves as the currency in which gold is denominated,resulting in a negative impact of USDI on GP.Notably,GP also demonstrates bidirectional causality,exhibiting both positive and negative effects on USDI.The analysis reveals that while a general inverse correlation persists between gold and the US dollar,this relationship transitions to positive during surges in global political and economic instability.In light of contemporary developments—including escalating geopolitical rivalries,tepid post-pandemic economic recovery,and elevated US interest rates driven by inflationary pressures—this study posit that the upward trajectory of gold prices retains a robust empirical foundation.展开更多
This paper selects the Corporate Social Responsibility(CSR)index from Hexun.com(2010–2020)and the stock price crash index of China’s Shanghai and Shenzhen A-share listed companies from the China Stock Market&Acc...This paper selects the Corporate Social Responsibility(CSR)index from Hexun.com(2010–2020)and the stock price crash index of China’s Shanghai and Shenzhen A-share listed companies from the China Stock Market&Accounting Research Database(CSMAR)for empirical analysis.By examining the impact of CSR performance on stock price crash risk,this study identifies key relationships and further investigates the moderating role of media promotion and communication as an intermediary to explore the transmission mechanisms and influence between the two.The empirical results indicate that CSR performance is significantly negatively correlated with stock price crash risk,suggesting that strong CSR performance can effectively reduce the likelihood of a stock price crash.Furthermore,additional analysis reveals that media plays a moderating role in the relationship between CSR performance and stock price crash risk.This study aims to contribute to the understanding of the formation mechanisms and analytical paradigms of factors influencing stock price crash risk while providing theoretical support and reference value for risk prevention strategies.展开更多
At the beginning of 2025,China’s national carbon market carbon price trend exhibited a continuous unilateral downward trajectory,representing a departure from the overall steady upward trend in carbon prices since th...At the beginning of 2025,China’s national carbon market carbon price trend exhibited a continuous unilateral downward trajectory,representing a departure from the overall steady upward trend in carbon prices since the carbon market launched in 2021.The analysis suggests that the primary reason for the recent decline in carbon prices is the reversal of supply and demand dynamics in the carbon market,with increased quota supply amid a sluggish economy.It is expected that downward pressure on carbon prices will persist in the short term,but with more industries being included and continued policy optimization and improvement,a rise in China’s medium-to long-term carbon prices is highly probable.Recommendations for enterprises involved in carbon asset operations and management:first,refining carbon asset reserves and trading strategies;second,accelerating internal CCER project development;third,exploring carbon financial instrument applications;fourth,establishing and improving internal carbon pricing mechanisms;fifth,proactively planning for new industry inclusion.展开更多
Motivated by a significant impact of price volatility on food security and economic stability inCameroon,this study aims to understand the factors influencing agricultural product price volatility(APPV)and formulateef...Motivated by a significant impact of price volatility on food security and economic stability inCameroon,this study aims to understand the factors influencing agricultural product price volatility(APPV)and formulateeffective policies for mitigating its negative impactand promoting sustainable economic growth.Specifically,this research used theautoregressive distributed lag-error correction model(ARDL-ECM)to analyse the impact of agricultural productivity,agricultural product imports,population,temperature variation,gross domestic product(GDP)per capita,and government expenditure on APPV based on the annual data from 2000 to 2021.The ARDL-ECM estimation results revealed that agricultural productivity(β=4.901),agricultural product imports(β=1.012),population(β=13.635),and GDP per capita(β=2.794)were positively related toAPPV,while temperature variation(β=-0.990)and government expenditure(β=-8.585)were negatively related toAPPVin the long term.However,temperature variation had a positive relationship with APPV in the short term.Moreover,the Granger causality test showed that there werebidirectional causality of APPV with agricultural productivityandagricultural product imports,and unidirectional causality of APPVwith population,temperature variation,GDP per capita,and government expenditure.The findings highlight the importance of public policies in stabilizing agricultural product prices by investing in agricultural research,improving access to agricultural inputs,strengthening farmer capacities,implementing climate adaptation measures,and enhancing rural infrastructure.Thesepolicies can reduce APPV,improve food security,and promote inclusive economic growth in Cameroon.展开更多
The IPO price suppression phenomenon is extremely common in both mature and emerging capital markets,and high price suppression can lead to an imbalance in the market supply and demand mechanism and affect the sustain...The IPO price suppression phenomenon is extremely common in both mature and emerging capital markets,and high price suppression can lead to an imbalance in the market supply and demand mechanism and affect the sustainable and healthy operation of the capital market.In the Chinese mainland market,the causes of IPO price suppression are mainly imperfect trading systems and information asymmetry.In this paper,we will use the survey method,literature analysis,and quantitative analysis to study the phenomenon of underpricing in the Chinese IPO market and its causes,comparing the Chinese IPO market with the U.S.IPO market.Using international and national statistics,we will propose the reasons affecting the IPO underpricing rate and compare the IPO underpricing difference between China and the US horizontally.Taking the Chinese A-share market as the main character,we analyze the impact of market transactions on IPO suppression and propose measures to improve IPO suppression in China's mainland stock market.展开更多
This paper analyzes the level, characteristics and existing problems of current electricityprice in China. Under the present circumstances the overall orientation of power price reform inthe 10th Five-year Plan period...This paper analyzes the level, characteristics and existing problems of current electricityprice in China. Under the present circumstances the overall orientation of power price reform inthe 10th Five-year Plan period should satisfy the requirements of power industry restructuring.Therefore, it is necessary to set up an appropriate pricing mechanism and system including thelinks of sales price to network, transmission and distribution price (T&D price) and sales price.In the light of various factors influencing increase and decrease in price, a forecast of electricitytariff is given in the five years to come.[展开更多
Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various ...Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users,the design of a reasonable dynamic pricing mechanism to actively engage users in demand response becomes imperative for power grid companies.For this purpose,a power grid-flexible load bilevel model is constructed based on dynamic pricing,where the leader is the dispatching center and the lower-level flexible load acts as the follower.Initially,an upper-level day-ahead dispatching model for the power grid is established,considering the lowest power grid dispatching cost as the objective function and incorporating the power grid-side constraints.Then,the lower level comprehensively considers the load characteristics of industrial load,energy storage,and data centers,and then establishes a lower-level flexible load operation model with the lowest user power-consuming cost as the objective function.Finally,the proposed method is validated using the IEEE-118 system,and the findings indicate that the dynamic pricing mechanism for peaking shaving and valley filling can effectively guide users to respond actively,thereby reducing the peak-valley difference and decreasing users’purchasing costs.展开更多
In this paper,we apply the spatial panel model to explore the relationship between the dynamic of two types of crude oil prices(WTI and Brent crude oil)and their refined products over time.Considering the turbulent mo...In this paper,we apply the spatial panel model to explore the relationship between the dynamic of two types of crude oil prices(WTI and Brent crude oil)and their refined products over time.Considering the turbulent months of 2011,when Cushing Oklahoma had reached capacity and the crude oil export ban removal in 2015 as breakpoints,we apply this method both in the full sample and the three resultant regimes.First,results suggest our results show that both WTI and Brent display very similar behaviour with the refined products.Second,when attending to each regime,results derived from the first and third regimes are quite similar to the full sample results.Therefore,during the second regime,Brent crude oil became the benchmark in the petrol market,and it influenced the distillate products.Furthermore,our model can let us determine the price-setters and price-followers in the price formation mechanism through refined products.These results possess important considerations to policymakers and the market participants and the price formation.展开更多
Productivity and international energy price shocks are reflected in PPI and CPI via industrial chains.China’s in-depth participation into the global value chains has increasingly lengthened its industrial production ...Productivity and international energy price shocks are reflected in PPI and CPI via industrial chains.China’s in-depth participation into the global value chains has increasingly lengthened its industrial production chains.The question is how the changing length of production chains will affect CPI and PPI,as well as CPI-PPI correlation?By constructing a global input-output price model,this paper offers a theoretical discussion on the impact of production chain length on the CPI-PPI divergence.Our findings suggest that the price shock of international bulk commodities has a greater impact on China’s PPI than that on CPI.The effects on both China’s PPI and CPI estimated by using the single-country input-output model are higher than the results estimated with the global input-output model.However,the difference between CPI and PPI variations estimated with the global input-output model is greater than the result estimated with the single-country input-output model,which supports the view that the lengthening of production chains,especially international production chains,leads to a divergence between CPI and PPI.Empirical results based on cross-national panel data also suggest that the lengthening of production chains has reduced the CPI-PPI correlation for countries,i.e.the lengthening of production chains has increased the PPI-CPI divergence.That is to say,policymakers should target not just CPI in maintaining price stability,but instead focus on the stability of both PPI and CPI.Efforts can be made to proactively adjust the price index system,and formulate the industrial chain price index.展开更多
基金funded in part by Grant No.DF-091-135-1441 from the Deanship of Scientific Research(DSR)at King Abdulaziz University in Saudi Arabia.
文摘In this paper,we propose STPLF,which stands for the short-term forecasting of locational marginal price components,including the forecasting of non-conforming hourly net loads.The volatility of transmission-level hourly locational marginal prices(LMPs)is caused by several factors,including weather data,hourly gas prices,historical hourly loads,and market prices.In addition,variations of non-conforming net loads,which are affected by behind-the-meter distributed energy resources(DERs)and retail customer loads,could have a major impact on the volatility of hourly LMPs,as bulk grid operators have limited visibility of such retail-level resources.We propose a fusion forecasting model for the STPLF,which uses machine learning and deep learning methods to forecast non-conforming loads and respective hourly prices.Additionally,data preprocessing and feature extraction are used to increase the accuracy of the STPLF.The proposed STPLF model also includes a post-processing stage for calculating the probability of hourly LMP spikes.We use a practical set of data to analyze the STPLF results and validate the proposed probabilistic method for calculating the LMP spikes.
文摘We often hear statements like“the market raises expectations for central bank interest rate cuts,resulting in higher commodity prices”.Given the current situation,the People’s Bank of China might adopt a more accommodative monetary policy to mitigate the impact of the China-U.S.trade friction.Will this further easing of the monetary environment lead to an increase in natural gas prices?
基金funded by the project supported by the Natural Science Foundation of Heilongjiang Provincial(Grant Number LH2023F033)the Science and Technology Innovation Talent Project of Harbin(Grant Number 2022CXRCCG006).
文摘Stock price prediction is a typical complex time series prediction problem characterized by dynamics,nonlinearity,and complexity.This paper introduces a generative adversarial network model that incorporates an attention mechanism(GAN-LSTM-Attention)to improve the accuracy of stock price prediction.Firstly,the generator of this model combines the Long and Short-Term Memory Network(LSTM),the Attention Mechanism and,the Fully-Connected Layer,focusing on generating the predicted stock price.The discriminator combines the Convolutional Neural Network(CNN)and the Fully-Connected Layer to discriminate between real stock prices and generated stock prices.Secondly,to evaluate the practical application ability and generalization ability of the GAN-LSTM-Attention model,four representative stocks in the United States of America(USA)stock market,namely,Standard&Poor’s 500 Index stock,Apple Incorporatedstock,AdvancedMicroDevices Incorporatedstock,and Google Incorporated stock were selected for prediction experiments,and the prediction performance was comprehensively evaluated by using the three evaluation metrics,namely,mean absolute error(MAE),root mean square error(RMSE),and coefficient of determination(R2).Finally,the specific effects of the attention mechanism,convolutional layer,and fully-connected layer on the prediction performance of the model are systematically analyzed through ablation study.The results of experiment show that the GAN-LSTM-Attention model exhibits excellent performance and robustness in stock price prediction.
文摘Global climate change has created substantial difficulties in the areas of sustainability,development,and environmental conservation due to the widespread dependence on fossil fuels for energy production.Nevertheless,the promotion of renewable energy programs has the potential to significantly expedite endeavors aimed at tackling climate change.Thus,it is essential to conduct a thorough analysis that considers the financial aspects to fully understand the main hurdles that are preventing the advancement of renewable energy initiatives.Italy is a leading country in the worldwide deployment of renewable energy.The objective of this research is to assess the impact of financial growth,economic progress,and energy expenses on Italy’s adoption of renewable energy sources.By employing the Auto-Regressive Distributed Lag(ARDL)technique,we analyzed annual data spanning from1990 to 2022.Findings revealed that a 1%increase in financial and economic development would boost renewable energy consumption in the long run by 0.29%and 0.48%,respectively.Instead,a 1%increase in energy prices might reduce consumption of renewable energy by 0.05%in the long run.This study’s primary significance lies in furnishing actionable strategies for Italy to augment green finance for renewable energy,fostering sustained social and economic progress.Moreover,the analytical insights gleaned from this research offer valuable insights for energy-importing nations worldwide.
文摘On April 2,the United States announced the implementation of the so-called“reciprocal tariffs”plan.Combined with factors such as the OPEC+plan to increase production starting in May,this led to a continuous plunge in the benchmark oil prices of WTI and Brent over the subsequent three trading days.Despite the significant impact of the United States’“reciprocal tariffs”plan on the global political and economic landscape,the fundamental dynamics of supply and demand remain the decisive factors in the fluctuations of international oil prices.The current trend of international oil price fluctuations is still primarily driven by the supply side,with both supply and demand factors playing a role.Investment,costs,and resource constraints on the supply side do not allow for a significant increase in crude oil production,while“consumption rigidity”on the demand side does not permit a significant decrease in crude oil demand.As a result,International oil prices are expected to fluctuate in the short term,but a significant decline is unlikely to be sustained in the near to medium term.In this context,Chinese oil companies should focus on four key areas to ensure the security of national oil and gas supplies:first,promoting high-quality increases in domestic oil and gas reserves and production;second,steadily strengthening the acquisition of overseas oil and gas resources;third,continuously driving innovation in oil and gas exploration and development technologies;fourth,enhancing the capacity for domestic oil and gas reserves in an orderly manner.
基金supported by the National Natural Science Foundation of China(Grant No.72401207 and 42101300)Beijing Municipal Education Commission,China(Grant No.SM202110038001).
文摘This paper investigates China's coal price volatility spreaders(CPVSs)from the supply side to locate the volatility source since coal price volatility may destabilize many downstream products'prices or even bring uncertainties to macroeconomic output.Especially in the carbon neutrality context,China's coal market is being reconstructed and responding to imbalances between supply and demand;identifying the CPVSs helps alleviate rising market instability and prevent energy-induced system risk.To achieve this objective,we explore causalities among 938 weekly coal prices reported by different coal-producing areas of China from 2006.9.4 to 2021.7.12 using the transfer entropy method.Then,coal price volatility influence is quantified to identify the CPVSs by conjointly using complex network theory and a rank aggregation method.The validity test demonstrates that the proposed hybrid method efficiently identifies the CPVSs as it correlates to many price determinants,e.g.,electricity and coal consumption and generation.The empirical results show that causalities among coal prices changed dramatically in 2016,2018,and 2020,affected by coal decapacity and carbon neutrality policies.Before 2018,coal-producing provinces with strong demand for coal and electricity,e.g.,Jiangxi,Chongqing,and Sichuan,were CPVSs;after 2019,those with comparative advantages in coal supply,e.g.,Gansu and Ningxia,were CPVSs.Overall,the coal market is unstable and sensitive to energy policy and external shocks.Policymakers and market participants are recommended to monitor and manage the CPVSs to improve energy security,avoid policy-induced instability and prevent risks caused by coal price fluctuations.
基金Research on Innovative Method of Drug Rational Use Supervision Decision Based on Big Data of Medical Insurance(Grant No.82273899)。
文摘Between 2016 and 2024,the Chinese government incorporated several innovative drugs into the National Reimbursement Drug List(NRDL)through price negotiations.These negotiations led to significant price reductions,which in turn stimulated an increase in sales.This study aimed to assess the impact of this policy on the pricing,utilization,and overall expenditure of targeted lung cancer therapies included in the NRDL.Using an interrupted time series analysis of procurement data from 698 healthcare institutions,the study evaluated both immediate and long-term effects.In terms of immediate effects,price negotiations resulted in a significant decline in the defined daily dose cost(DDDc)for all targeted therapies(P<0.05).Regarding long-term trends,a significant shift was observed only in the pricing trajectory of Gefitinib,Icotinib,and Ensartinib(P<0.05).In terms of immediate effects on drug utilization,all targeted medicines experienced a substantial increase in volume(P<0.05),except for Gefitinib and Icotinib.Over the long term,the usage of all targeted therapies exhibited a significant upward trend(P<0.05).With respect to expenditure,the immediate impact of NRDL inclusion resulted in a significant increase in spending on Afatinib,Crizotinib,Osimertinib,Alectinib,and Ensartinib(P<0.05).Over time,total spending on targeted medicines showed a significant increase(P<0.05),except for Erlotinib.Overall,NRDL price negotiations successfully reduced the economic burden on lung cancer patients,improving both accessibility and affordability of targeted therapies in China.
文摘While the significant role of technological innovation in promoting renewable energy has been extensively explored in the literature,limited attention has been paid to the impact of energy patents,particularly clean energy patents and fossil fuel patents.This study pioneers an investigation into the effects of energy patents and energy prices on renewable energy consumption.The study utilizes data from 2000Q1 to 2023Q4 and,due to the nonlinear nature of the series,applies wavelet quantile-based methods.Specifically,it introduces the wavelet quantile cointegration approach to evaluate cointegration across different quantiles and time horizons,along with the wavelet quantile-on-quantile regression method.The results confirm cointegration across different periods and quantiles,highlighting the significant relationships between energy patents,economic factors,and renewable energy consumption.Furthermore,we found that fossil energy patents negatively affect renewable energy consumption,while clean energy patents have a similar but weaker effect,especially in the short term.In addition,higher energy prices promote renewable energy adoption while economic growth positively influences renewable energy consumption,particularly in the short term.The study formulates specific policies based on these findings.
基金Innovation Team Project of Liaoning Institute of Science and Technology:“Smart Economy Practice and Innovation Team”College Students’Innovation and Entrepreneurship Training Program Projects:“Research on the Application of Big Data Analysis Tools”and“Zhice Quantitative Investment Studio”+2 种基金Teaching and Research Project:“Research on the Path of AI-Enabled Undergraduate Education and Teaching Reform Based on the Needs of Liaoning’s Revitalization and Development(Project No.:LKJY202510)”Teaching Reform Project:“Research and Practice on the Evaluation of Digital Talents in Application-Oriented Universities(Project No.:LNKJ202412)”Project of Liaoning Federation of Social Sciences:“Research on the Key Elements and Practical Paths of Educational Digital Transformation(Project No.:2025lslybkt-050)”。
文摘Based on the financial data and stock price information of Bengang Steel Plates Co.Ltd.from 2004 to 2023,this paper uses SPSS 26 software,combined with DuPont Analysis and Wall Score Method,to explore the correlation between stock price and nine key financial indicators selected from three dimensions:profitability,development capability,and operating capability,including fixed asset growth rate,price-to-book ratio(P/B ratio),and gross profit margin.Through correlation analysis,multiple regression analysis,and curve fitting,the study finds that:fixed asset growth rate,P/B ratio,and gross profit margin show a significant positive correlation with stock price;return on equity(ROE),operating income,and accounts receivable turnover days show a significant negative correlation with stock price;earnings per share(EPS)and net profit growth rate do not show a significant correlation with stock price.The research results indicate that the stock price of Bengang Steel Plates Co.Ltd.is greatly affected by its asset scale and market valuation,while some profitability indicators have not been effectively transmitted to the stock price.Finally,countermeasures and suggestions are put forward from the aspects of cost control,technological innovation,market expansion,and financial structure optimization,so as to provide references for corporate operation and investment decisions.
文摘Fluctuations in real estate prices are closely linked to the macro-economy,exerting a profound influence on social investment and consumption levels.As a key source of funding for the real estate market,bank credit significantly affects housing price changes in major Chinese cities.This paper explores the transmission mechanisms and pathways of bank credit on real estate prices through theoretical analysis and empirical research.It constructs a panel regression model to empirically analyze the relationship between bank credit scale and housing prices in 35 large and medium-sized Chinese cities from 2012 to 2022,assess the impact of credit on housing price fluctuations,and compare differences between first-tier and second-tier cities.Based on these findings,the paper proposes suggestions for regulating housing prices by controlling credit scale,aiming to deepen the understanding of the relationship between bank credit and housing prices and support the stable development of China’s macro-economy and real estate market.
基金Project of National Social Science Fund of China(Project No.:23BGJ010)。
文摘This study examines the dynamic interplay between the US Dollar Index(USDI)and gold prices(GP)to assess the sustainability of gold price trends.Employing a rolling window bootstrapping causality test methodology across full and sub-samples,the findings of this study challenge the conventional assumption of a stable long-term inverse correlation between USDI and GP,thereby validating the hypothesis that their relationship is nonlinear and time-dependent.During periods of heightened geopolitical and economic volatility,both the US dollar and gold function as safe-haven assets,with USDI fluctuations exerting a positive influence on GP.Conversely,under stable market conditions,the US dollar serves as the currency in which gold is denominated,resulting in a negative impact of USDI on GP.Notably,GP also demonstrates bidirectional causality,exhibiting both positive and negative effects on USDI.The analysis reveals that while a general inverse correlation persists between gold and the US dollar,this relationship transitions to positive during surges in global political and economic instability.In light of contemporary developments—including escalating geopolitical rivalries,tepid post-pandemic economic recovery,and elevated US interest rates driven by inflationary pressures—this study posit that the upward trajectory of gold prices retains a robust empirical foundation.
基金R&D Program of Beijing Municipal Education Commission(Grant No.SM202210005007)。
文摘This paper selects the Corporate Social Responsibility(CSR)index from Hexun.com(2010–2020)and the stock price crash index of China’s Shanghai and Shenzhen A-share listed companies from the China Stock Market&Accounting Research Database(CSMAR)for empirical analysis.By examining the impact of CSR performance on stock price crash risk,this study identifies key relationships and further investigates the moderating role of media promotion and communication as an intermediary to explore the transmission mechanisms and influence between the two.The empirical results indicate that CSR performance is significantly negatively correlated with stock price crash risk,suggesting that strong CSR performance can effectively reduce the likelihood of a stock price crash.Furthermore,additional analysis reveals that media plays a moderating role in the relationship between CSR performance and stock price crash risk.This study aims to contribute to the understanding of the formation mechanisms and analytical paradigms of factors influencing stock price crash risk while providing theoretical support and reference value for risk prevention strategies.
文摘At the beginning of 2025,China’s national carbon market carbon price trend exhibited a continuous unilateral downward trajectory,representing a departure from the overall steady upward trend in carbon prices since the carbon market launched in 2021.The analysis suggests that the primary reason for the recent decline in carbon prices is the reversal of supply and demand dynamics in the carbon market,with increased quota supply amid a sluggish economy.It is expected that downward pressure on carbon prices will persist in the short term,but with more industries being included and continued policy optimization and improvement,a rise in China’s medium-to long-term carbon prices is highly probable.Recommendations for enterprises involved in carbon asset operations and management:first,refining carbon asset reserves and trading strategies;second,accelerating internal CCER project development;third,exploring carbon financial instrument applications;fourth,establishing and improving internal carbon pricing mechanisms;fifth,proactively planning for new industry inclusion.
文摘Motivated by a significant impact of price volatility on food security and economic stability inCameroon,this study aims to understand the factors influencing agricultural product price volatility(APPV)and formulateeffective policies for mitigating its negative impactand promoting sustainable economic growth.Specifically,this research used theautoregressive distributed lag-error correction model(ARDL-ECM)to analyse the impact of agricultural productivity,agricultural product imports,population,temperature variation,gross domestic product(GDP)per capita,and government expenditure on APPV based on the annual data from 2000 to 2021.The ARDL-ECM estimation results revealed that agricultural productivity(β=4.901),agricultural product imports(β=1.012),population(β=13.635),and GDP per capita(β=2.794)were positively related toAPPV,while temperature variation(β=-0.990)and government expenditure(β=-8.585)were negatively related toAPPVin the long term.However,temperature variation had a positive relationship with APPV in the short term.Moreover,the Granger causality test showed that there werebidirectional causality of APPV with agricultural productivityandagricultural product imports,and unidirectional causality of APPVwith population,temperature variation,GDP per capita,and government expenditure.The findings highlight the importance of public policies in stabilizing agricultural product prices by investing in agricultural research,improving access to agricultural inputs,strengthening farmer capacities,implementing climate adaptation measures,and enhancing rural infrastructure.Thesepolicies can reduce APPV,improve food security,and promote inclusive economic growth in Cameroon.
文摘The IPO price suppression phenomenon is extremely common in both mature and emerging capital markets,and high price suppression can lead to an imbalance in the market supply and demand mechanism and affect the sustainable and healthy operation of the capital market.In the Chinese mainland market,the causes of IPO price suppression are mainly imperfect trading systems and information asymmetry.In this paper,we will use the survey method,literature analysis,and quantitative analysis to study the phenomenon of underpricing in the Chinese IPO market and its causes,comparing the Chinese IPO market with the U.S.IPO market.Using international and national statistics,we will propose the reasons affecting the IPO underpricing rate and compare the IPO underpricing difference between China and the US horizontally.Taking the Chinese A-share market as the main character,we analyze the impact of market transactions on IPO suppression and propose measures to improve IPO suppression in China's mainland stock market.
文摘This paper analyzes the level, characteristics and existing problems of current electricityprice in China. Under the present circumstances the overall orientation of power price reform inthe 10th Five-year Plan period should satisfy the requirements of power industry restructuring.Therefore, it is necessary to set up an appropriate pricing mechanism and system including thelinks of sales price to network, transmission and distribution price (T&D price) and sales price.In the light of various factors influencing increase and decrease in price, a forecast of electricitytariff is given in the five years to come.[
基金supported in part by Technology Project of State Grid Jiangsu Electric Power Co.,Ltd.,China,under Grant J2022011.
文摘Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users,the design of a reasonable dynamic pricing mechanism to actively engage users in demand response becomes imperative for power grid companies.For this purpose,a power grid-flexible load bilevel model is constructed based on dynamic pricing,where the leader is the dispatching center and the lower-level flexible load acts as the follower.Initially,an upper-level day-ahead dispatching model for the power grid is established,considering the lowest power grid dispatching cost as the objective function and incorporating the power grid-side constraints.Then,the lower level comprehensively considers the load characteristics of industrial load,energy storage,and data centers,and then establishes a lower-level flexible load operation model with the lowest user power-consuming cost as the objective function.Finally,the proposed method is validated using the IEEE-118 system,and the findings indicate that the dynamic pricing mechanism for peaking shaving and valley filling can effectively guide users to respond actively,thereby reducing the peak-valley difference and decreasing users’purchasing costs.
文摘In this paper,we apply the spatial panel model to explore the relationship between the dynamic of two types of crude oil prices(WTI and Brent crude oil)and their refined products over time.Considering the turbulent months of 2011,when Cushing Oklahoma had reached capacity and the crude oil export ban removal in 2015 as breakpoints,we apply this method both in the full sample and the three resultant regimes.First,results suggest our results show that both WTI and Brent display very similar behaviour with the refined products.Second,when attending to each regime,results derived from the first and third regimes are quite similar to the full sample results.Therefore,during the second regime,Brent crude oil became the benchmark in the petrol market,and it influenced the distillate products.Furthermore,our model can let us determine the price-setters and price-followers in the price formation mechanism through refined products.These results possess important considerations to policymakers and the market participants and the price formation.
基金the Special Project of the National Science Foundation of China(NSFC)“Open Development of China’s Trade and Investment:Basic Patterns,Overall Effects,and the Dual Circulations Paradigm”(Grant No.72141309)NSFC General Project“GVC Restructuring Effect of Emergent Public Health Incidents:Based on the General Equilibrium Model Approach of the Production Networks Structure”(Grant No.72073142)+1 种基金NSFC General Project“China’s Industrialization Towards Mid-and High-End Value Chains:Theoretical Implications,Measurement and Analysis”(Grant No.71873142)the Youth project of The National Social Science Fund of China“Research on the green and low-carbon development path and policy optimization of China’s foreign trade under the goal of‘dual carbon’”(Grant No.22CJY019).
文摘Productivity and international energy price shocks are reflected in PPI and CPI via industrial chains.China’s in-depth participation into the global value chains has increasingly lengthened its industrial production chains.The question is how the changing length of production chains will affect CPI and PPI,as well as CPI-PPI correlation?By constructing a global input-output price model,this paper offers a theoretical discussion on the impact of production chain length on the CPI-PPI divergence.Our findings suggest that the price shock of international bulk commodities has a greater impact on China’s PPI than that on CPI.The effects on both China’s PPI and CPI estimated by using the single-country input-output model are higher than the results estimated with the global input-output model.However,the difference between CPI and PPI variations estimated with the global input-output model is greater than the result estimated with the single-country input-output model,which supports the view that the lengthening of production chains,especially international production chains,leads to a divergence between CPI and PPI.Empirical results based on cross-national panel data also suggest that the lengthening of production chains has reduced the CPI-PPI correlation for countries,i.e.the lengthening of production chains has increased the PPI-CPI divergence.That is to say,policymakers should target not just CPI in maintaining price stability,but instead focus on the stability of both PPI and CPI.Efforts can be made to proactively adjust the price index system,and formulate the industrial chain price index.
