Abstract:The reconfiguration of the global production system after the 2008 financial crisis, as well as the long-term, disproportionately high economic growth across different regions in China, highlighted the importance of China’s new development pattern of “dual circulation” as a key strategy for promoting high-quality economic development. Conducting a scientific industry relocation is the main approach to constructing the “dual circulation”. As a result, the industry gradient coefficient (IGC) is increasingly adopted to support decision making in industry relocation. This paper theoretically demonstrates that the IGC can be used to reveal the direction of industry relocation. After that, a newly proposed approach is adopted to test its accuracy. It is found that the first-order difference of the IGC is a qualified indicator of the direction of industry relocation. Its accuracy is not affected by the time span or by the relocation opposite to the changes in competitive advantages, but is mainly impacted by the hysteresis of relocation and the buffering effect for industries with a huge advantage. On the other hand, the hysteresis of relocation grants the predictive ability to the industry gradient coefficient.

Abstract:This paper explores whether international trade frictions force Chinese firms to enhance their innovative activities. Empirical results from global anti-dumping and anti-subsidy sanctions imposed on Chinese firms as exogenous shocks show that the innovative activities of Chinese firms increase significantly after experiencing trade frictions. Moreover, the positive relationship between trade frictions and corporate innovation is more significant in highly export-oriented firms,firms facing stronger competition, and high-tech firms.This suggests that trade importance, competitive pressure, and high-tech features motivate firms to engage more in corporate innovation in response to trade frictions. Results also show that the reverse push effect of trade frictions on innovation is more pronounced in firms with more technical talents, in firms that are less financially constrained, and in state-owned enterprises,as these firms are equipped with more abundant innovative resources. Further analyses show that international trade frictions give rise to relatively high-quality innovations, and this effect can last for up to four years. And boosting innovation activities helps relieve the negative impact of trade frictions on firms’export performance. Our research not only contributes to the literature on corporate innovation and international trade frictions, but also provides practical guidance for China’s transformation from a manufacturing giant to a manufacturing powerhouse. Besides, our conclusions may also offer theoretical implications for the recent heated discussions on how to cope with Sino-US trade frictions.

Abstract:A deep exploration of the energy conservation and emission reduction potential of the industrial symbiosis system, along with promoting cross-industry and cross-regional synergistic consumption and utilization of multi-source solid waste, is an important tool for addressing the compound environmental pollution problems of heavy industries and population-dense areas, such as the Beijing-Tianjin-Hebei Region. At present, the scientific design of a systematic industrial symbiosis solution that matches the spatial characteristics of regional waste generation and discharge faces three major challenges: Unclear data on multi-source solid waste generation and discharge, unclear symbiosis pathways, and difficulties in assessing the energy conservation and emission reduction potential of the industrial symbiosis solution. The purpose of this study is to use the Beijing-Tianjin-Hebei Region as an example to construct a spatial map of multi-source solid waste generation and discharge. Based on this, a complex system optimization method is introduced to develop a multi-source solid waste cross-industry and cross-region symbiotic utilization plan. Finally, the environmental and economic performance of the plan is quantitatively evaluated using a bottom-up approach, with key symbiotic regions, enterprises, and technologies identified. The methodology of this study is expected to provide a replicable model for the spatial and refined management of industrial symbiosis in other regions and even across the country.

Abstract:Data has become one of the essential driving forces for value production in the digital era, and accelerating the cultivation of the data-factor market has become an important strategy for the growth of China’s digital economy. Meanwhile, data is a competitive advantage for firms. The paper explores a scenario where a single data supplier exists in the data market, with two competing firms on the demand side.Competing firms can obtain the same data from the data supplier, and put it into production to provide consumers with personalized products. The paper investigates data purchase strategies of demand-side firms and finds that, for competing demand-side firms, data-driven product personalization intensifies price competition in the product market, reduces firm profits, and increases consumer welfare. The optimal strategy for the data supplier is to sell to both competing firms when offering a uniform price and selling to only one firm when he provides differentiated prices to maximize his profit. Our findings have implications for the formulation of the data market’s trading rules, participation strategies of the demand side, and data pricing strategies for the supply side.

Abstract:The natural rate of interest, defined as the equilibrium real interest rate in an ideal, frictionless economy, serves as a critical real interest rate anchor for price-based monetary policy. The difference between the real interest rate and the natural rate of interest, referred to as the “natural rate gap”, contains valuable information about economic fundamentals and the central bank’s monetary policy, which plays an important role in the pricing of treasury bonds. The paper estimates China’s natural rate of interest through a semi-structural macroeconomic model and finds that the natural rate gap is informative for forecasting treasury bond excess returns. Specifically, the higher the natural rate gap, the higher the excess returns on China treasury bonds. In contrast to findings in developed financial markets, variations in the natural rate gap explained by macroeconomic variables do not exhibit significant predictive power for bond excess returns in China. This suggests that macroeconomic fundamentals are not fully priced into China’s treasury bonds market. To further investigate the mechanism behind the return predictability of the natural rate gap, this paper analyzes it from the perspective of yield-oriented investors. Due to tax considerations on capital gains and other factors, commercial banks, which are the primary holders of China treasury bonds, tend to hold bonds till maturity and may place more emphasis on yield to maturity rather than expected return. Both theoretical and empirical results suggest that commercial banks’demand for treasury bonds is a key mechanism through which the natural rate gap influences bond pricing. Overall, this paper not only presents new insights into the cyclical characteristics of the natural rate of interest but also offers perspectives on the pricing mechanisms of treasury bonds.

Abstract:Based on market microstructure theory, this study develops a model in which rational informed traders trade against rational uninformed traders and noise traders in a one-shot game within a rational expectations equilibrium (REE) framework. In this model, each informed trader is connected with some other (e.g., k) informed traders, sharing his private information with them while also obtaining their private information. That is, he and his k connected informed traders mutually share their private information before trading. However, the informed traders are assumed to never share or deliver any information to the uninformed traders, who can only learn information from the risky asset’s price. With this information-sharing network, this study aims to analyze the implications of informed traders’ limited information sharing for rational traders’ strategic trading behavior and the consequent asset pricing quality, including price discovery efficiency and market liquidity. The results are as follows. First, with exogenous information acquisition, an informed traders’ demand schedule consists of a speculative part and a market-making part. Because their information sharing does not change the precision of each private signal, the intensity of speculative trading remains unchanged, while the intensity of market-making is negatively affected by the extent of information sharing, k. The rational uninformed traders’ trading strategy includes only market-making part, whose trading intensity equals that of the informed traders. Second, information sharing among informed traders results in more informed trading, leading to more information being incorporated into the clearing price and thus boosting price discovery efficiency. Information sharing aggravates information asymmetry between informed and uninformed traders. However, this effect is alleviated and outweighed by the resulting greater price informativeness, as it enables uninformed traders to learn more information by observing the price. Consequently, the market liquidity gets better. On the other hand, with endogenous information acquisition, information sharing creates a strategic substitution or complementarity effect in rational traders’ information acquisition choices within the information market equilibrium, which impacts trading behaviors and, consequently, asset pricing outcomes. Price discovery efficiency increases with the informed traders’ information sharing, while market liquidity is not linearly affected by the information sharing. Specifically, in an unclear market situation where the ex-ante risk of the traded risky asset is higher and/or the noise trading is greater, market liquidity improves with information sharing. In contrast, in a relatively clearer market situation where the ex-ante risk of the traded risky asset is lower and/or the noise trading is less, market liquidity is U-shaped in its response to information sharing among informed traders. In summary, this study extends the research of information sharing network theory from the perspective of market microstructure theory and helps illustrate the implications of information sharing and dissemination on social media and networks for the security market more comprehensively and objectively. The findings of this study also provide some theoretical insights on how to regulate and guide investors’ information sharing on social media and networks to maintain market liquidity and accelerate price discovery in the securities market.

Abstract:In recent years, the price of industrial and commercial land in China has shown a continuous upward trend. In this context, an important question is whether the good news of rising land value can be recognized by investors and how it will affect the equity financing behavior of companies. This paper empirically tests this question using data from 14 305 land transactions between listed firms and local governments from 2006 to 2016. The empirical results show that the higher the land value owned by a listed firm, the greater the probability of increased equity financing in the following year, and the larger the scale of financing. This conclusion remains valid even after addressing the endogenous issues. Secondly, there is a significant negative correlation between land value and the cost of equity capital. Thirdly, investor attention can positively moderate the relationship between land value and equity financing. Furthermore, the group test shows that when the debt level of listed firms is high, land value has a significant positive impact on equity financing. When the debt level is low, land value has no significant impact. Finally, we find that firms with higher land value can adjust to the target capital structure more quickly. The results of this paper imply that changes in the land market can be transmitted to the capital market, affecting the financing behavior of listed firms.

Abstract:This paper examines how zombie firms shift their debt within the supply chain, following the 2015 supply-side structural reform in China. Findings reveal that zombie firms, particularly state-owned ones, are decreasing their reliance on bank loans while increasing the use of trade credit, effectively passing their debt to non-zombie firms in the supply chain. This debt shifting leads to higher unpaid invoices for suppliers in industries with a high proportion of zombie customers. This phenomenon cannot be explained by credit redistribution, but rather by the stronger negotiation power of zombie firms and the willingness of suppliers to share risk due to policy shocks. While the supply-side reform curtails ineffective “blood transfusions” from banks to zombie firms, it leads to an increase in the occupation of funds in the supply chain by zombie firms, thereby squeezing out investments from upstream efficient firms. These findings provide new insights into the impacts of zombie firms and the effects of the supply-side reform. It is suggested that the government should prevent zombie firms from shifting their debt to suppliers, thereby shielding healthy firms from harmful spillover effects.

Abstract:Recently under the rapid development of Internet syndicated loan, it has become an important part of credit market. The literature mainly analyzes the impact of internet syndicated loans on credit market and banks’ risk taking strategy, but the perspective of cooperation mechanism is rarely studied. This paper constructs a theoretical model and analyzes the impact of the Internet syndicated loans on the credit market from perspective of cooperative mechanism. The results show that: 1) The Internet syndicated loans cooperative mechanism makes Internet financial institution prefers borrowers with higher loan interest rates which have higher risk;. 2) Traditional commercial bank independently risk management reduces credit market risk, and increases the scale of the credit market; 3) The Internet syndicated loans cooperation mechanism makes traditional commercial banks less likely to do independently risk management. Based on these conclusions, we suggest that the regulator sets an upper limit on the fee ratio charged by Internet financial institutions to traditional banks, so as to improve the willingness of doing independently risk management by traditional commercial banks and reduce the risks of the credit market.

Abstract:Online singing platforms have attracted many users to sing and publish songs online. Accurate singing-song recommendation systems are essential to enhance user experience and stickiness for such platforms. User’s vocal ability is one of the major factors to consider in the recommendation model. However, how to predict a user’s vocal ability is challenging. Meanwhile, online singing platforms provide social networking services. How to utilize the social feedback information to improve recommendation performance is worth studying. To address these issues, this paper proposes new methods to predict a user’s vocal ability on a song and to model social feedback factors. Further, a novel model for singing-song recommendations is developed. Experiments conducted on a real-world dataset demonstrate the effectiveness of our proposed model and the necessity of modeling vocal ability and social feedback factors to improve recommendation performance.

Abstract:Decision theory is the foundational theory in economics and management for studying human judgment and decision-making behaviors. Some researchers have won the Nobel Memorial Prize in economic sciences for their outstanding contributions to the field of decision theory. Currently, with the growing influence of artificial intelligence and data science on decision-making, both the theoretical and applied research in decision theory are facing new challenges and opportunities. This paper analyzes the contributions of the Nobel Laureates in economic sciences in decision theory and shows their main research topics, which focus on utility theory, social choice theory, and behavioral decision theory. Motivated by these classical theories, our analysis focuses on the transformation of research paradigms in the specific area of decision theory from the perspective of the intersection among artificial intelligence, data science, and classical decision theory. A data-driven intelligent decision-making research paradigm is developed from the perspectives of “utility learning”, “preference evolution”, and “intelligent decision interpretability”. Its differences from the classical decision theory research paradigm are highlighted. Moreover, the applications of data-driven intelligent decision-making in economics and management are discussed.