Commodity is an important part of industrial production and financial investment, and accurate commodity price forecasting is of great significance to safeguard industrial production and help investors avoid risks. However, most of the existing commodity price forecasting models are point-value models based on closing prices, which ignores the volatility information. Therefore we propose a heteroskedasticity threshold autoregressive interval model with exogenous variables (HTARIX) and apply it to the commodity markets. We also construct a test statistic based on interval-valued data to test whether there is conditional heteroskedasticity in the model, and propose a generalized minimum $D_K$ distance estimation. The advantage of our model is that it can capture the conditional heteroskedasticity and nonlinear features of interval-valued time series models. Compared with the point-valued models, our method contains more information of the data. The empirical results imply that HTARIX model performs better than other comparative models in interval-valued commodity price forecasting.
This paper studies how environmental regulation affects the sustainable economic development through an angle of soft constrains of environmental regulation. We first develop a theoretical model, based on the threshold effect of innovation investment, to introduce the role of soft constrains of environmental regulation into the theoretical framework of Porter hypothesis, and analyze how the soft constraints of environmental regulation affect enterprise competitiveness. Using policy change of the SO2 emission charges from 2007 to 2014, we examine the Porter hypothesis by adopting a DID estimation. We find evidence that state owned enterprises have more significant soft constraint problems than non-state owned firms, which weaken incentives for innovation investment, and then hurt enterprise competitiveness. However, we find strong evidence of the existence of Porter hypothesis for no-state owned firms.
To implement the instructions from General Secretary Xi Jinping regarding "enhancing the effciency of funding for the National Natural Science Foundation, " the Department of Management Sciences conducted a series of research activities, systematically analyzing the funding effectiveness of the distinguished young scholars and outstanding young scholars talent projects. A total of 556 survey questionnaires were designed and distributed, and 233 experts participated in the discussion. Utilizing statistical methods such as the coeffcient of variation, the difference-in-differences, and the natural language processing, the survey data were quantitatively analyzed. The statistical analysis of the survey data showed the following key findings: First, compared to other talent projects like outstanding young scholars, the comprehensive funding effectiveness of distinguished young scholars is relatively higher. After approval, there is a significant improvement in both academic achievements and academic influence. Second, there is heterogeneity in the funding effectiveness among talent projects like distinguished young scholars and outstanding young scholars. Third, scholars who receive distinguished young scholars funding before the age of 42 experience a greater improvement in comprehensive funding effectiveness. Based on these analysis, recommendations are proposed, emphasizing the need to "strengthen process management and project closeout management" for talent projects.
Based on the personal characteristics of listed companies from 2009 to 2021, including directors, supervisors and other senior managers, this paper identifies executives with environmental protection background and studies their impact on the ESG rating of the current year and the next year. The study finds that good environmental protection background of the directors, supervisors and senior managers of listed companies can significantly improve the ESG rating of the current year and the next year. And this effect is affected by the power and interest correlation. Moreover, with the implementation of the new Environmental Protection Law, compared with other enterprises, the ESG rating of enterprises with executives with environmental protection background has significantly improved after 2015. The analysis of different dimensions of ESG shows that the improvement of ESG rating by executives with environmental protection background mainly lies in the dimensions of environmental and social responsibility. Mechanism analysis shows that executives with environmental protection background can improve ESG rating in two ways: One is to increase the probability of passing ESG related motions at shareholders' meetings; the other is to improve the enterprise environmental protection system. The results of heterogeneity analysis based on equity ownership, industry and historical rating show that the improvement effect of executives with environmental protection background on ESG rating of enterprises is mainly concentrated in state-owned enterprises, polluting industries and enterprises with low historical rating.
Based on the external impact of anti-corruption since the 18th CPC National Congress, the difference in difference (DID) method is used to analyze the impact of anti-corruption on land investment of listed real estate companies using the micro land transaction data. It is found that the overall cumulative abnormal returns of listed real estate companies from land transaction are significantly reduced. After anti-corruption, the cumulative abnormal returns increase significantly, the administrative expenses decrease significantly, the land prices increase significantly, and the investment effciency improves significantly. For the samples of state-owned and non-state-owned companies, there are significant differences in the impact of anticorruption, and the improved effciency of land investment is more pronounced for non-state-owned companies. Finally, in order to improve the market environment of land transaction, we give policy suggestions from the perspective of enterprise heterogeneity.
As the core of industrial data in the System of National Accounts (SNA), input-output data is the key database for economic structural analysis. Now, National Bureau of Statistics in China has started to reform the input-output accounting system. In this context, this paper analyzes the main features of the accounting framework revealed through the transformation process of the thoughts of SNA accounting systematically, from Anglo-American dominance in the early period to European dominance later. Based on the analysis, it illustrates that their main difference focuses on production accounting, which leads to the introduction of input-output accounting into SNA and its subsequent development. Along the theoretical path, we can better understand the changes of input-output accounting systems, and the reasons why different systems are employed in EU and the United States. Then, based on the interpretation, we can then correctly understand the great theoretic and practical significances of input-output accounting reform for the improvement of our country' s national accounting framework at the current situation, as well as for the service to economic structure transformation analysis in China. Further, it helps us identify the direction and path of the reform. On the basis of the above analysis, some suggestions are put forward for the reform of input-output accounting based on the reality of China and the useful practices in other countries.
The financial market is changing rapidly, and quantitative investment strategies need to be adjusted and optimized in a timely manner. The fusion model can dynamically adjust the weights of the model and the way of combination according to the market changes to achieve adaptive adjustment and optimization. In this paper, three different fusion two-layer Stacking models are constructed based on three different Boosting class algorithms, namely LightGBM, Adaboost, and XGBoost, and empirical analyses of stock picking backtesting are carried out on CSI 300 constituent stocks to compare and select the most suitable base learning model and the best fusion effect of the secondary model. The empirical results show that the three different fusion models outperform the single-algorithm models in stock market prediction, with the best performance being the fusion model where the base learners are the XGBoost and LightGBM algorithms, and the AdaBoost algorithm is used as the secondary learner. When the number of holdings is 20, the average annualized income is 13.57%, the Shape ratio is 1.23, and the maximum retracement is 0.48. In addition, the results of this backtest show that the fusion model has better adaptability and effectiveness in times of high market volatility. This study can provide investors with a new way of thinking about investment, and also provides some insights into how to promote the use of fusion models in financial practice.
The Lorentz curve of income group data is fitted with finite
From the perspective of magnitude, direction and dynamics, this paper investigates the tail risk contagion among 10 important stock markets in the world from 1997 to 2022 based on the tail risk interconnectedness network, which is constructed by combining the time-varying peak over threshold (POT) model and the spillover index model. We also focus on the characteristics of tail risk spillover network and the internal mechanism of tail risk contagion. Empirical results show that the average tail risk spillover index of these 10 markets reached 59.79% during the whole sample period, indicating obvious cross-market contagion effect of tail risk. At the same time, the tail risk spillover effect is time varying, which is more significant during the crisis. The United States is the largest net exporter of tail risk in the sample range and one of the important sources of extreme risk in the international market. Due to relatively low degree of openness, the Chinese mainland market has the lowest level of two-way tail risk spillovers and has been a net recipient of tail risk for a long time. Since the outbreak of the China-US trade frictions and the COVID-19, the tail risk linkages among the international stock markets have been strengthened, bringing greater challenges to preventing imported risks and maintaining financial security and stability. The structure of the international tail risk spillover network is also timevarying. The spillover effect mainly exists between developed markets during stable periods, while it is significantly strengthened between emerging markets during crises. Finally, the economic fundamentals and the market contagions are both found to be important factors of tail risk spillover effects.
In the general line of coordinated development between the goal of carbon peak carbon neutrality and the goal of energy transformation proposed by the 20th National Congress, the development of renewable energy is the core path and inevitable choice, and the financing scale and financing effciency in the financial market all affect the development of regional renewable energy. In view of this, this paper selected the panel data of 31 provinces and cities in China from 2009 to 2018 as samples, and empirically tested the impact mechanism of financial resources on regional renewable energy development by constructing two-way fixed effect models, intermediary effect models and threshold effect models, and thoroughly analyzed the intermediary effect and threshold effect in the impact path. The empirical results show that: Financial development can significantly drive the growth of regional renewable energy, but this effect has a U-shaped nonlinear threshold feature, only when the financial development level exceeds a certain threshold, can it show an effective driving ability; the influence of financial development on the growth of renewable energy in the region has significant regional heterogeneity, in which the west is the strongest, the east is the second, and the central is the weakest. Financing scale and technological innovation play a full mediating effect between financial development and regional renewable energy growth. The research conclusions of this paper provide theoretical basis and policy reference for China to achieve the goal of "double carbon", promote the development of regional renewable energy, and build a green financial system, which has important theoretical and practical value.
To analyze the relation between institutional difference and pricing mechanism by cross-listed asset is of significant theoretical and practical value for deepening capital market reform and optimizing resource allocation. Based on monthly data from 147 Chinese mainland and Hong Kong dual-listed stocks over the past 20 years, our empirical results reveal that, after controlling for major influencing factors, the AH premium has a significantly negative impact on future returns of A-shares but does not significantly impact the future returns of H-shares. The impact of the AH premium on the future returns of A-shares is mainly concentrated in stocks with fewer arbitrage restrictions, and stocks with higher AH premiums have higher shortselling balances in the following month. These results indicate that due to differences in institutions and investor structures, A-shares experience greater volatility and are more prone to pricing errors compared to H-shares, and the pricing ability of the AH premium stems from arbitrageurs engaging in reverse trading against the mispricing in A-shares. This study, for the first time, considers the AH premium as a pricing factor and provides evidence and mechanisms for its pricing ability, expanding the understanding of the pricing mechanism of cross-listed stocks.
The coordinated development of government guiding funds and their operating environment holds significant importance in resolving market failures in resource allocation and promoting the quality and effciency of regional economic development. This study revealed the coupling and coordination relationship between government guiding funds and their operating environment, through the calculation of the government guiding funds operational effciency in each stage of "fundraising, investment management, and exit" and the evaluation of operational environment level in various dimensions of "innovation, finance, industry, people's livelihood and fiscal". The study discovered that, in general, the government guiding funds and their operating environment have entered the initial phase of coordinated development. Among them, the level of coupling and coordination between the two is relatively insuffcient in the stage of the management, investment and exit; the coupling and coordination relationship between the innovation environment and the stages of management, investment and exit stay imbalanced; the high-level development of the fiscal environment represents the principal factor contributing to the elevated level of coupling and coordination between the two systems in the eastern region, but it cannot solve the problem of ineffcient exit of the eastern government guiding funds. To encourage the development of a highly coordinated approach between government guiding funds and their operating environment, the central and western regions should give priority to enhancing the innovation environment. The eastern region needs to focus on improving the operational capacity of large-scale funds; The government guiding funds require systematic operation and management to prevent the exit dilemma resulting from the accumulation of risks.
