In the face of multiple challenges both domestically and internationally, stabilizing market confidence and maintaining a positive outlook among the public are of paramount importance for economic development. Understanding how economic agents' expectations are formed, grasping the transmission channels of expectations in the economy, and accurately assessing the significance of various anticipated shocks on economic fluctuations are the foundations for effective expectation management. A substantial body of literature has discussed the relationship between expectation changes and macroeconomic fluctuations by constructing Dynamic Stochastic General Equilibrium (DSGE) models, considering expectations as a significant factor influencing macroeconomic fluctuations. However, asset prices, which are crucial channels for the transmission of expectations, often receive insufficient attention in discussions of expectations. The connection between asset prices and expectations is close: on one hand, changes in asset prices reflect changes in economic agents' expectations of future economic fundamentals; on the other hand, expectations and the formation of asset prices are closely intertwined. Macroeconomic fluctuations or changes in economic fundamentals can affect economic agents' expectations, subsequently influencing their investment decisions and other choices, ultimately manifesting in asset prices. Therefore, exploring whether asset prices contribute to understanding the role of expectations in the Chinese economy is not only theoretically important for clarifying the relationship between asset prices, anticipated shocks, and macroeconomic fluctuations but also holds practical significance for stabilizing public expectations and promoting stable economic development.
This paper constructs a New Keynesian DSGE model, incorporating settings that reflect the unique characteristics of the Chinese economy and introducing multiple long-run anticipated shocks. Bayesian estimation serves as the foundation for quantitative analysis, with macroeconomic data and asset price data (stock prices and market interest rates) being used to estimate the model. This paper demonstrates that the information contained in asset prices is helpful in accurately assessing the impact of anticipated shocks on the Chinese economy. First, we compare estimation results of unconditional variance decompositions and second-moment results of key model variables between datasets that include asset price data and those that do not. We find that asset price data contain additional information about expectations, aiding in the correct identification and evaluation of the impact of anticipated shocks on economic fluctuations in China. Then, based on the estimated results with asset prices, this paper further decomposes forecast error variances for both macroeconomic and asset price variables. It reveals that anticipated shocks can explain more than 50% of output, consumption, and investment fluctuations, as well as nearly all asset price fluctuations. Different variables exhibit varying degrees of sensitivity to expectations over time, with asset prices being the most sensitive. Subsequently, the paper contrasts the differences between long-run anticipated shock processes and short-run anticipated shock processes, demonstrating long-run anticipated shock processes have advantages in model fitting. Finally, through welfare analysis, the paper finds that incorporating a response to asset prices in monetary policy can effectively mitigate welfare losses resulting from anticipated shocks.
The contributions of this paper to the existing literature are followings: firstly, it bridges the gap between research on anticipated shocks and asset prices, emphasizing the need to consider asset price data that are sensitive to expectations when studying anticipated shocks. Secondly, there is limited consideration of long-run shock processes in both domestic and international research on business cycles. This paper conducts a detailed comparison of the model fitting of long-run and short-run shock processes to the Chinese economy, demonstrating the advantages of using long-run anticipated shocks in fitting Chinese macroeconomic and asset price data. Lastly, the paper employs welfare analysis to suggest that when facing economic fluctuations dominated by expectation factors, policy authorities adopting more flexible and diverse monetary policies, such as incorporating asset price factors into monetary policy rules, may effectively improve overall welfare.

Industrial policies are widely employed by the government as a critical economic practice. However, the economic influence and operational mechanisms of industrial policies have long been topics of debate in academia. Concurrently, Chinese entrusted loans have experienced substantial growth in recent years, making it an important factor that cannot be ignored. The operational mechanisms of entrusted loans have attracted considerable attention from policymakers and scholars. Previous studies have demonstrated that industrial policies can affect the real economy through formal financial channels, such as bank credit and equity financing. However, limited studies have investigated the effect of industrial policies on the real economy through the channel of entrusted loans. This gap in the literature has led to insufficient understanding of whether and how entrusted loans play a role in the transmission process of industrial policies.
On the basis of key industrial policies outlined in the central government's “Five-Year Plan,” this paper investigates the role of entrusted loans in the transmission process of industrial policies. We find that listed manufacturing firms supported by industrial policies issue more entrusted loans than their counterparts without such support. Furthermore, these entrusted loans are predominantly allocated among industries supported by industrial policies mainly through an equity correlation mechanism. The effect of industrial policies on encouraging manufacturing firms to use entrusted loans is more pronounced for firms located in areas with greater government intervention, industries with high-capacity utilization rates, and industries with low independence from external finance. Moreover, we find that contracts between manufacturing firms operating within the same supported industries tend to be less restrictive. They not only issue larger and longer-term entrusted loans but also demand lower interest rates.
This paper contributes to the literature in two main aspects. First, it examines the influence of industrial policies on manufacturing firms. Empirical analyses using Chinese data reveal that industrial policies significantly increase the participation of manufacturing firms in entrusted loan activities. These entrusted loans effectively alleviate the financial constraints faced by small-and medium-sized enterprises (SMEs) operating within policy-supported industries, thus promoting the overall development of these industries. These empirical results fill the gap in the literature by providing evidence of the role of entrusted loans in the transmission process of industrial policies. This expands our understanding of how industrial policies affect the real economy from the perspective of entrusted loans.
Second, this paper contributes to the literature examining the operational mechanisms of entrusted loans. This study reveals that manufacturing firms within policy-supported industries issue entrusted loans to firms in the same industries through an equity correlation mechanism. These entrusted loans are characterized by their large scale, long-term nature, and low-interest rates, highlighting their role in capital allocation in policy-supported industries. Moreover, the advantages of information supervision due to equity correlation can effectively alleviate information asymmetry between lenders and borrowers, resulting in more entrusted loan contracts between equity-related firms. Overall, our results emphasize the role of entrusted loans as a supplement to the formal finance system.
This study offers policy insights on how to streamline the transmission process of industrial policies and fully leverage their potential for financially supporting real enterprises. When implementing industrial policies, the government can provide financial support to firms that serve critical roles in the industrial chain, such as listed manufacturing firms. Explore supply chain finance and other ways to increase the financing support for SMEs.Create a sound business environment for SMEs and increase their bank credit support .

In recent decades, the Chinese banking sector has experienced substantial and rapid growth, especially in terms of total bank assets. However, there remains a gap between the current situation of commercial banks and the requirements for achieving the high-quality development of the banking system in various respects, including innovation ability and service quality. This situation suggests the presence of deep-seated problems related to structural imbalances and financial resource misallocation in Chinese commercial banks. Therefore, it is necessary to evaluate the performance of the internal operations of banks using a scientific approach.
The conventional data envelopment analysis (DEA) approach treats the operational processes of commercial banks as a “black box,” lacking the capability to reveal complicated internal operational processes by which inputs become outputs. This limitation persisted until the development of the network DEA approach. Although numerous studies have used the network DEA approach to examine the efficiency of Chinese commercial banks, they typically adopt independent or relational constraints when evaluating the relationship between successive sub-stages. These approaches fail to capture potential conflicts or tend to generate the wastes of intermediates. In addition, most of the studies decompose the internal operational structure of commercial banks into two sub-stages, raising funds and using funds, or only focus on a single type of business, such as assets, liability, and off-balance sheet activities. Although a simplified model offers advantages in terms of calculation and operability, it may not be able to fully and effectively evaluate the operational efficiency of commercial banks that have complex operational structure in reality.
To fill the aforementioned research gap, this paper uses a cooperative additive slacks-based measure (SBM) network DEA model that effectively integrates the background of financial structural reform. We include 108 Chinese commercial banks from 2013 to 2019 as samples to evaluate their internal operational efficiency based on the perspective of structural decomposition. The operation process of a commercial bank is divided into four sub-stages: using initial funds, raising funds and conducting intermediate business, using funds, and generating profits. The last stage is further subdivided into two parallel stages, accounting for the generation of interest income and other non-interest income, respectively. Our findings reveal the presence of structural imbalances in the operation process of Chinese commercial banks, including uneven efficiency in each sub-stage and uncoordinated operation in adjacent sub-stages. Specifically, commercial banks perform well in two stages, using initial funds and using funds, but require enhancements in the profit generation stage. In terms of the efficiency of input, output, and intermediate products, the input efficiency of fixed assets and the output efficiency of non-performing loans and other non-interest net incomes are lower. The lack of coordination between the sub-stages of banks leads to misallocations of employees, branches, deposits, earning assets and other factors. Comparing the efficiency of various types of commercial banks, we find that foreign banks exhibit the highest overall efficiency, with relatively balanced efficiencies across sub-stages. However, the efficiency of individual sub-stages fluctuates considerably. Although large state-owned banks perform well in the initial fund raising stage, this is at the expense of generating redundant employees and branches. Moreover, joint-stock commercial banks allocate more resources to traditional business, resulting in some redundancy in deposits and earning assets. Further, our scale efficiency analysis reveals that the scale efficiency of large state-owned banks is lower than that of other types of banks, with a downward trend observed during the study period.
On the basis of the findings, we propose three policy implications. First, with the deepening of financial structural reform, commercial banks are encouraged to improve their operational efficiency, weak business links, and financial supply capacity. Second, through scientific and technological empowerment and platform construction, the current operational structure of commercial banks can be reformed by optimizing intermediate products and controlling the cost of fixed assets and the risk of non-performing loans. Such reforms would enable the rational allocation of resources and enhance the stability of banks' internal structure. Third, to contribute to financial structural reform, different types of banks should tailor their efforts to optimize their operational structures and improve operational performance based on their specific shortcomings. Encouraging resource-sharing among different types of banks to facilitate mutual learning and improve overall efficiency, sub-stage efficiency, and performance stability is recommended.

The emerging literature suggests that the accounting information disclosed by micro-enterprises is useful for macro forecasting. Previous studies have mainly analyzed the relevance of aggregate accounting information for predicting macroeconomic indicators, such as future GDP growth, job creation and destruction, monetary policy, and inflation (Konchitchki and Patatoukas, 2014a; Crawley, 2015; Luo et al., 2016; Shivakumar and Urcan, 2017; Rouxelin et al., 2018; Ma and Zhang, 2020; Ye et al., 2020; Hann et al., 2021). However, little is known about the usefulness of aggregate accounting information in predicting meso-level indicators, especially the credit risk of the regional banking industry.
The non-performing loan ratio is a leading indicator of an impending banking crisis (Reinhart and Rogoff, 2011) and can effectively reflect a bank's risk status (Fang, 2015). Thus, this paper investigates the predictive value of changes in aggregate Ponzi Interests for the growth of non-performing loans in commercial banks. This study uses data from publicly listed companies to construct a measure of firm Ponzi Interests, considering the primary repayment source and subsequently aggregating this measure to the provincial level. We measure Ponzi Interests by tracking the financial sources of firms' interest payments over an extended period and separating the component of total cumulative interest payments covered by financing cash inflows.
Consistent with our conjecture, we find that changes in aggregate Ponzi Interests effectively predict the subsequent growth of non-performing loans in commercial banks. We observe a significantly positive association between changes in aggregate Ponzi Interests and the subsequent growth of non-performing loans in commercial banks at the provincial level. This relationship is attributed to the fact that our Ponzi Interests indicator reflects the reliability of a firm's primary repayment source. Firms with a deepening degree of Ponzi Interests will have a higher operating risk and likelihood of experiencing financial distress. Furthermore, the increase in non-performing loans in commercial banks is primarily driven by firms experiencing a deterioration in their financing capacity and asset profitability as well as firms lacking affiliations with banks. Moreover, the findings of a cross-sectional analysis reveal that the forecasting power of the aggregate Ponzi Interests indicator is more pronounced in provinces where Ponzi financing sustainability is poorer and banks have less incentive and ability to conceal non-performing loans.
Our paper contributes to the literature in three aspects. First, it introduces an innovative approach by constructing a regional aggregate Ponzi Interests indicator based on the primary repayment source of firms. In addition, this study establishes the relationship between changes in aggregate Ponzi Interests and the subsequent growth of non-performing loans in commercial banks. By delving into enterprise cash flow and the ability to pay interest, our paper extends the research on the meso and macro predictive value of accounting information (Konchitchki and Patatoukas, 2014a; Crawley, 2015; Luo et al., 2016; Shivakumar and Urcan, 2017; Rouxelin et al., 2018; Ma and Zhang, 2020; Ye et al., 2020; Hann et al., 2021).
Second, this paper enhances the literature on the prediction of firms' financial distress and default risk. Previous studies in this field have mainly focused on the predictive value of financial indicators (Altman, 1968), short-term cash flow (Aziz et al., 1988), and market return (Beaver, 1966) information. Our study provides evidence that the Ponzi Interests indicator based on long-term cash flow information can be effectively used to predict corporate default risk.
This paper complements the literature on bank risk-taking determinants. We examine how accounting information about the reliability of a firm's primary repayment source influences a bank's passive risk-taking, thereby affecting changes in non-performing loans. Given that the literature has mainly focused on the effects of macroeconomic conditions and bank characteristics on banks' passive risk-taking, this paper provides additional insights from the perspective of firms acting as loan demanders.
This paper has crucial policy implications and practical relevance. Our results suggest that aggregate Ponzi Interests derived from micro-enterprises' accounting data contain valuable information regarding future credit risk and expected credit losses associated with bank credit assets. These findings imply that regulators should consider the Ponzi Interests indicator to enhance their credit supervision. In addition, commercial banks should incorporate the Ponzi Interests indicator in their specific loan approval procedures and expected credit loss models.

Since 2020, China has experienced a number of bond defaults. Notably, Henan Yongmei Group, an AAA-rated bond issuer, unexpectedly declared a default of one-billion-yuan super and short-term commercial paper, triggering discussions on disorderly defaults and “debt evasion.” In this context, it is essential to understand the impact of bond defaults to mitigate bond default risks and foster the healthy growth of the Chinese bond market.
Theoretically, a bond default can have two effects on other local bonds. First, the information effect is driven by shared economic fundamentals or implicit guarantees from local governments. A bond default reveals additional information about fundamentals or implicit guarantees, thereby impacting bonds in the same region. Second, the flight effect arises from investors' fund reallocation from high-risk assets to low-risk assets, especially to local low-risk assets when local segmentation exists in the bond market, to reduce their risk exposure.
To investigate these effects in the Chinese bond market, this paper categorizes credit bond defaults in China between 2014 and 2020 into state-owned enterprise (SOE) bonds and private enterprise bonds. We empirically analyze the impacts of these bond defaults on local issuers' bond spreads in the secondary market and their bond issuance in the primary market. The results support the presence of both the information and flight effects.
First, we find that SOE defaults adversely affect local SOE bonds and private enterprise defaults adversely affect local private enterprise bonds. In both cases, this leads to an increase in yield spreads and a decrease in subsequent issuances by the corresponding type of issuers within the same province. This finding is consistent with the prediction of the information effect. Second, we observe that private enterprise defaults positively affect yield spreads and the subsequent issuance of local SOE bonds. This finding aligns with the flight effect. Third, we identify disorderly defaults, which deviate from market expectations, and quantify their information effect. Compared with orderly defaults by SOEs, disorderly defaults by SOEs exert a more substantial adverse impact on local SOE bonds. Although orderly defaults by private enterprises exert a positive impact on local SOE bonds, their disorderly defaults have a negative impact on local SOE bonds. This finding indicates that disorderly defaults can amplify the adverse information effect, which dominates the positive flight effect in magnitude.
Based on the aforementioned findings, we make three policy recommendations. First, the presence of the flight effect indicates that the Chinese bond market still encounters local segmentation. We believe that such local segmentation stems from the current dominance of banks' participation and local governments' inclination to channel local financial resources within their regions, leading to local banks displaying a preference for local corporate bonds. To address this, the construction of a unified national market is imperative to facilitate the complete circulation of bond funds across the country. This will require a reduction in the control of local governments over financial institutions and an increase in the participation of institutional investors in the bond market to change the bank-dominated situation.
Second, the flight effect reflects that investors still perceive SOE bonds to be safer than private enterprise bonds, indicating the existence of implicit guarantees enjoyed by SOEs. To prevent the flight effect from aggravating financing structural imbalances between SOEs and private enterprises, it is crucial to effectively address the soft budget constraint faced by SOEs, allowing both private enterprises and SOEs to compete fairly for financing opportunities.
Lastly, disorderly defaults exacerbate the adverse impact of bond defaults. For bond issuers, engaging in “debt evasion” behaviors, such as not providing risk warnings and preemptively transferring assets, can cause increased debt costs and future challenges with bond issuance. Furthermore, ignoring market principles will ultimately lead to market penalties. Therefore, it is imperative to enhance the timely tracking and information disclosure of bond default risks.
This paper makes three main contributions. First, considering both the information and flight effects, we demonstrate the presence of a regional flight effect in the Chinese bond market. This reveals that local segmentation still exists in the Chinese bond market. Furthermore, banks, as primary investors, prefer to localize resources, restricting the complete flow of funds across the country. Second, we distinguish the heterogeneous impact of bond defaults between SOEs and private enterprises. Third, we distinguish between expected and unexpected defaults, revealing that unexpected defaults have more severe negative impacts.

The repo market plays a crucial role in the stabilization of financial markets and the transmission of monetary policies. Since the global financial crisis in 2008, scholars have increasingly focused on the performance of the repo market.
In China, the repo market has experienced rapid growth and has become a key component of the financial system. The existing literature mainly focuses on the impact of the repo market on bond pricing and its regulations. Few studies have examined the microstructure of China's repo market.
This paper fills this gap by examining high-frequency intraday repo rate movements in China's interbank repo market using transaction-level data. Our data consist of close to ten million transactions from February 2015 to June 2021. With this unique dataset, we find that the overnight repo rate demonstrates the following robust W-shaped intraday pattern: The rate initially decreases, then rises, declines again, and finally increases once again. Our detailed findings are summarized as follows.
First, the repo rate typically starts at a fixed high level at 9∶00 and declines until 10∶00. We compare the repo rate of transactions between all institutions and the rate between banks only and find that they do not significantly differ in the first hour. This result indicates that transactions during this period are mainly among banks, which are less likely to default and use safer collateral. Because of the high opening rate, the market seeks an equilibrium rate during this period, resulting in the observed declining pattern.
Second, the repo rate increases from 10∶00 to 12∶00. We attribute this increase to the participation of non-bank institutions, which are riskier and thus face higher repo rates. In China, holidays and weekdays are usually concatenated, effectively turning weekends into working days; these are defined as working weekends in our paper. On working weekends, banks continue to operate normally, whereas most non-bank institutions are closed. Taking advantage of this unique institutional setup, we demonstrate that the increase in the repo rate almost disappears when non-bank institutions are absent from the market.
Third, the repo rate declines again from 15∶00 to 16∶30. In addition to explanations based on volatility and liquidity from the existing literature, we identify that this pattern is driven by banks' intraday liquidity management. Banks need to retain intraday liquidity to accommodate potential withdrawals by firms. Only in the late afternoon, when firms are not likely to withdraw, banks will lend their surplus funds in the repo market, leading to a decline in the repo rate. We conduct an event study by examining repo rate movements on the deadline days for corporate tax payment. The results reveal that the decline between 15∶00 and 16∶30 is significantly larger before a tax payment due date than after it, when banks do not need to maintain extra liquidity in the late afternoon. Our results indicate that the oversupply of liquidity resulting from banks' liquidity management contributes to the repo rate decline in this period.
Our paper has crucial implications for regulators and market participants. First, our findings are useful for the construction of benchmark interest rates. This paper shows that the repo market is volatile and may not have efficient pricing between 9∶00 and 10∶00 and between 16∶30 and 16∶50. Thus, market organizers should consider excluding this period when constructing the benchmark rate. Second, this paper provides empirical evidence for the importance of improving banks' liquidity management. The empirical results show that banks' intraday liquidity hoarding contributes to the decline in the repo rate between 15∶00 and 16∶30. As the main supplier in the repo market, banks' liquidity management is closely related to the efficiency of this market.

The outbreak of the COVID-19 pandemic has posed challenges to medical security and healthcare systems, intensifying the urgency for residents' demand for medical security. In theory, unavoidable risks influence residents' demand for different insurance types. According to risk temperance theory, individuals encountering unavoidable risks also tend to reduce their exposure to irrelevant risks. Studies have demonstrated that Chinese residents experienced a significant increase in healthcare demand during the pandemic. However, traditional commercial insurance, which is an integral component of healthcare, did not experience a proportional increase in sales. In the context of pandemic prevention efforts, the effective provision of inclusive healthcare for residents has become an urgent issue that cannot be overlooked.
In recent years, China has witnessed the emergence of a new inclusive healthcare type, known as mutual aid, driven by the rapid development of insurance technology (InsurTech). Mutual aid incorporates InsurTech techniques, such as big data, artificial intelligence, and blockchain, to optimize risk management, underwriting, and claims settlement processes. Thus, it significantly reduces the manual costs associated with medical security and possesses certain inclusive characteristics. Given the impact of the pandemic, mutual aid, with its inclusive traits, may play a more prominent role than traditional commercial insurance. First, mutual aid operates entirely online, leveraging InsurTech, and is thus more resilient to disruptions caused by the pandemic compared with offline institutions. Second, mutual aid offers comparable coverage at lower premiums than traditional commercial insurance, making it particularly suitable for underdeveloped areas and individuals with low income. This expands mutual aid's reach and enables responsive protection for underdeveloped regions. Moreover, based on blockchain technology, mutual aid functions in a decentralized manner, utilizing the retrospective sharing of coverage amounts among participants instead of upfront premium collection. This design also alleviates liquidity pressure on participants' payments and offers advantages amid pandemic-induced economic impacts. Thus, we hypothesize that mutual aid and traditional commercial insurance will exhibit different performance patterns under the influence of the pandemic. Investigating the underlying mechanisms of mutual aid is an important academic endeavor for comprehending the application of InsurTech in China and facilitating the transformation of the traditional insurance industry. Over the past few years, mutual aid has experienced rapid growth in China, reaching a peak membership of 200 million. Despite the regulatory authorities suspending such programs to maintain industry order and manage risks, the role of InsurTech and mutual aid in enhancing medical security in the post-pandemic era remains significant.
Using monthly data collected from 100 cities between January 2019 and May 2020, covering the period from one year prior to the pandemic outbreak until the end of its initial wave, this study compares the development of traditional commercial insurance and online mutual aid during the COVID-19 pandemic. The empirical findings are as follows. First, the scale of mutual aid correlates positively with the number of local cumulative cases. Specifically, for every increase of 100 confirmed cases during the sample period, the average number of participants in mutual aid increases by 7,446 and the compensation paid grows by 4.27%. However, traditional insurance exhibits no significant changes in sales. Second, mutual aid plays a more significant role in regions with better digital financial inclusion and among populations with a higher level of social trust. Third, mutual aid has a more pronounced effect on migrants and females who are disproportionately affected during the pandemic.
These results have crucial implications for the development of insurance and social security systems. First, this study provides empirical evidence highlighting the positive response of InsurTech during the pandemic, which is highly relevant for policymaking. In particular, in the context of normalized pandemic prevention and control, mutual aid empowered by InsurTech effectively overcomes the limitations of traditional commercial insurance in terms of accessibility and inclusiveness, thus becoming a vital supplement to traditional commercial insurance. Second, this study indicates the necessity for digital transformation in the traditional commercial insurance industry. Although mutual aid has been completely discontinued, the InsurTech mechanism underlying it offers vital insights for reforming traditional commercial insurance. This is the first study to empirically examines how mutual aid functions within China's medical security system and provides specific guidance for healthcare system reform following the discontinuation of mutual aid.

M&A is an important function of the capital market and an important force in the external governance of companies. Market-oriented M&A and restructuring is conducive to “revitalizing the stock of listed companies, improving quality and efficiency, and transforming development”. Especially in the context of the full implementation of the registration system for stock issuance in China in early 2023, the M&A and restructuring of listed companies in the A-share market has become more active. In order to resist malicious takeovers, more and more listed companies have added anti-takeover clauses by amending their articles of association. According to data from Juchao Information Network, more than 2,000 A-share listed companies added or amended anti-takeover clauses in their articles of association between 2015 and 2022 to enhance the intensity of anti-takeover. By setting up anti-takeover clauses, listed companies have increased the cost of acquirers, reduced the threat of hostile takeovers, and ensured their long-term stable development. The existing studies on the impact of anti-takeover clauses on corporate governance and investment decisions are mainly divided into two views: the “long-term value creation” hypothesis and the “management rift effect” hypothesis. The former suggests that anti-takeover clauses promote high quality management to invest more actively in long-term innovation projects; the latter suggests that anti-takeover clauses make management more likely to prefer personal interests over corporate investment strategies, thus reducing the value of the firm. It can be seen that there is no unanimity in the academic community on the topic of how anti-takeover clauses affect corporate decision making and value.
For micro enterprises, talent is the first resource, innovation is the first driving force, and human capital is the fundamental support for enterprises to achieve innovation-driven and high-quality development. Therefore, from the perspective of high-level human capital of enterprises, this paper constructs firm-level anti-takeover intensity indicators from anti-takeover clauses in the manually collected articles of association of listed companies to study the impact of anti-takeover intensity on the structure of human capital of enterprises, taking A-share listed companies from 2011-2019 as a sample. It is found that the impact of anti-takeover intensity on human capital structure has a U-shaped relationship, i.e., anti-takeover intensity significantly inhibits the enhancement of corporate human capital structure when it is low, while it has a boosting effect on the enhancement of corporate human capital structure when the intensity of anti-takeover provisions exceeds a critical value. The mechanism test finds that when the intensity of anti-takeover is low, the short-sightedness of management dominates, which inhibits the improvement of human capital structure; when the intensity of anti-takeover exceeds the threshold, the anti-takeover “barrier” reduces the threat of acquisition, which helps to improve the job satisfaction of employees and reduce the brain drain. In addition, an increase in the intensity of anti-takeover will also encourage companies to focus more on long-term development, thus increasing human capital investment and adjusting the human capital structure. Further study found that the impact of anti-takeover intensity on human capital structure varies by firm type and nature of ownership.
The marginal contributions of this paper are mainly as follows: first, this paper enriches the research on anti-takeover clauses by manually collecting and organizing and establishing a database of anti-takeover clauses of listed companies from 2011-2019, and for the first time, the impact of anti-takeover clauses on the behavioral decisions of corporate employees and employee hiring from the perspective of human capital structure on the basis of constructing anti-takeover intensity indicators of listed companies; second, The findings of this paper indicate a U-shaped relationship between anti-takeover clauses and corporate human capital, and the robustness of the results of this paper is verified by the number of recent wars in each city and the number of anti-takeover clauses in neighboring companies collected manually as instrumental variables of anti-takeover intensity, which provides useful exploration for subsequent empirical studies on anti-takeover clauses to alleviate the endogeneity problem; third, this paper further explores the channels of the impact of anti-takeover clauses on human capital structure from the perspectives of employee satisfaction, human capital investment and management short-sightedness, and the findings indicate that the long-term stable development of enterprises is an important factor influencing the internal human capital structure, which not only provides corresponding internal logic and empirical evidence for how enterprises can realize talent-intensive enterprises, but also provides a useful tool for China's regulatory authorities to improve the legal system of anti-takeover clauses, the function of capital market and perfect the modern enterprise system with Chinese characteristics.

A green, sustainable, and low-carbon economy is not only an inevitable choice for China but also a powerful impetus for the global economy to move toward higher quality. The establishment of systems and mechanisms that encourage green investment and discourage polluting investment is the key to promoting the green transformation of China's economic development model, and also plays a vital role in implementing the Carbon Peak and Carbon Neutrality Goals. As an emerging green investment concept, environmental, social, and governance (ESG) investment has gradually gained the attention of investors who seek to align economic benefits with social values.
Investors worldwide are adapting to the new low-carbon and green financial landscape, which offers substantial opportunities for ESG investment. Although there has been a considerable increase in green financing and the volume of green bonds issued, the supply of equity products that conform to the investment philosophy of ESG remains limited, providing investors with few choices. An important reason is that ESG investment poses a new challenge to traditional investment models and portfolio theory. As a crucial technological step in equity-based ESG investment, the research on portfolios based on ESG integration is still far from comprehensive.
From the perspective of investors, the integration of the concept of ESG investment into traditional financial frameworks has become a research hotspot. The ESG integration strategy, as the fastest-growing ESG investment strategy, has gradually attracted attention in both practical and academic circles due to its quantitative approach. Research on ESG investment in China is still in its infancy, and there is limited research on the ESG investment portfolio model. However, with the continuous promotion of green finance policies and improvement of ESG information disclosure systems, the quality of available ESG data is gradually improving. Moreover, the demand for equity-type ESG investment is bound to continue to increase. Thus, designing an investment portfolio model based on the ESG integration strategy and analyzing changes in investors' behavior have become key issues that need to be addressed urgently, forming the focus of this research.
From the perspective of investor utility, we establish a portfolio model based on the ESG integration strategy for institutional investors that considers budget constraints, industry constraints, and restrictions on short selling. The ESG penalty term is used in the model to reflect the investor's preference for the ESG level of individual stocks. In addition, we analyze changes in investor behavior under the condition of considering ESG preferences theoretically. When only budget constraints are factored into the model, we provide an explicit solution that illustrates the portfolio selection for ESG-oriented investors. Furthermore, after introducing ESG attributes to assets, we analyze the preference priorities of investors for different assets. In terms of parameter selection, we use the Lagrange method to establish the relationship between ESG levels and preference coefficients for portfolios. To validate the model and understand the sources of returns in ESG portfolio models, we use ESG ratings data from the Chinese stock market for the comparative analysis of the models. According to the four mainstream ESG rating methods available in the market, we construct high-medium-low ESG benchmark portfolios and then conduct a comparative analysis of different ESG portfolio models through numerical experiments.
We find that (1) considering ESG utility can change investors' investment behavior and asset portfolio choices, with higher ESG-rated assets receiving greater allocation weights. (2) As ESG levels increase, the ESG-effective frontier surface shows a significant rightward shift. This indicates that investors who consider ESG utility are willing to sacrifice some returns to obtain compensation for ESG utility at the same risk level. (3) The investment portfolio model based on ESG integration effectively weighs risk, returns, and green sustainability, promoting high-quality development in the investment industry. (4) The presence of significant inconsistency in ESG ratings within China's stock market may introduce risks to active portfolio management. This papers helps to understand the impact of inconsistent ESG ratings on investment portfolios based on ESG integration and provides valuable insights for institutional investors to make the informed use of ESG rating information for active portfolio management, thereby indirectly supporting the green and low-carbon transformation of listed companies.
We analyze portfolio models under ESG integration strategies and provide theoretical and empirical evidence for the micro-foundations of green finance research in China, with several policy implications. First, in the process of systematically promoting carbon peaking and carbon neutrality goals in China, it is necessary to emphasize the role of institutional investors in the transformation of corporate value growth when investing in ESG. Second, good ESG performance is not always necessarily associated with better investment returns. To achieve established goals at the ESG level, it is necessary to appropriately relinquish some benefits. Finally, institutional investors should focus on the issue of inconsistent ESG ratings, which have a significant impact on active portfolio management based on ESG and are directly related to the success or failure of investment strategies. This also reflects that the current construction of China's ESG investment ecology still needs to be improved. Regulatory authorities, rating agencies, and data service institutions need to promote further improvement in ESG information disclosure.

The futures market plays a fundamental role in asset price discovery. Improving the efficiency of asset price discovery would help enhance financial market efficiency, reduce information acquisition costs for investors, and promote finance's positive effects on the real economy. China's Futures and Derivatives Law, which came into effect in 2022, indicates the importance of developing the futures market to raise its price discovery function. The cost-of-carry model, a classical futures pricing model, reveals the relationship between futures and spot prices only when there are infinite arbitrageurs. However, this model is not suitable when dealing with limited arbitrageurs and does not illustrate the micro-mechanism of information aggregation in the futures market. Although empirical research indicates that price discovery efficiency in the financial futures market is higher than that in the spot market, a robust theoretical foundation for this relationship is lacking. Thus, we develop a futures pricing model, where informed traders, cross-market arbitrageurs, and noise traders trade within a rational expectations equilibrium framework, to investigate the pricing outcomes of spot and futures markets, characterize the interactions between different types of investors, and uncover the micro-mechanisms of information aggregation in the futures market, the determinants of the price discovery function of spot and futures markets.
Given that futures delivery is earlier than the liquidation of spot in the real financial world, we assume that the spot is traded in each period and futures are only traded in the first period in a two-period trading model. The spot is liquidated after the end of the second period and the futures contract is delivered at the equilibrium price of spot in the second period. Informed traders and arbitrageurs exist in the spot and futures markets, but only arbitrageurs can trade across markets. Under these assumptions, we first solve the partial market equilibrium without cross-market arbitrageurs. In this equilibrium, we analyze how delivery risk affects informed trading behaviors in the futures markets and how private information is incorporated into futures prices. In addition, we determine how spot-futures spread occurs from the perspective of information structure and inventory risk. Subsequently, we solve the overall market equilibrium by considering the cross-market arbitrageurs' strategy. In the overall equilibrium, we examine the factors determining arbitrage intensity, the impact of the number of arbitrageurs on the spot-futures spread, and the relationship between arbitrage trading and price discovery efficiency. Finally, we empirically test the model's findings by analyzing the impact of COVID-19 on the price discovery of CSI 300 index futures in China.
This study yields the following results. First, the price discovery of futures is determined by informed traders and noise traders rather than by arbitrageurs. The price discovery level of spot is better than that of futures when the precision of private information and noise trading in the two market is equal. Second, the greater the information aggregation efficiency of a spot at the delivery stage of the futures, the higher the price discovery level of futures. Third, when private information in the futures market is more precise than that in the spot market, the liquidity of futures is positively related to its price discovery and the relative impact of arbitrage trading on asset prices is negatively correlated with its price discovery efficiency. Finally, we determine that COVID-19 reduces the price discovery function of stock index futures due to increased investor concerns regarding short-term stock index volatility.
This paper contributes to the futures pricing literature in three aspects. First, by incorporating informed traders and noise traders, we construct a model that is more suitable for analyzing the price discovery function of futures within the framework of the rational expectations equilibrium. This model provides a theoretical basis for previous empirical analyses and suggests avenues for further research. Second, many existing studies assume no-arbitrage exogenously, which limits their ability to analyze the differential impact of arbitrage trading on spot and futures prices and the resulting price discovery efficiency. We address this limitation by endogenizing arbitrage strategies. Third, we empirically examine how investors' expectations about the underlying asset's price volatility affect the price discovery level of futures, providing an empirical basis for our theoretical model. Based on these findings, future research could explore the choices of informed traders between trading in the spot market or futures market and investigate investors' decisions to roll over their positions on the delivery date to further examine futures pricing.

According to the Seventh National Census, in 2020, the total fertility rate of Chinese women of childbearing age was 1.3, which is lower than the generational replacement level of 2.1. China has entered the era of “low fertility”. Thus, the formulation of supportive policies to unlock fertility potential, meet fertility desires, and enhance fertility rates has become a crucial topic of concern across all societal sectors.
A key factor contributing to the low fertility rate is the trade-off that women encounter between their career and childbearing desires. Few studies have examined the role of grandparenting, a common practice among Chinese families, in alleviating this conflict and increasing fertility rates. In addition, the literature on fertility decision-making only discusses how individuals determine the number of children they have, often overlooking the fact that individuals also have to decide their childbearing age, which is another vital dimension of fertility decision-making.
This paper presents an endogenous population growth model that encompasses grandparenting, individual occupation and fertility trade-offs. Using data from China Family Panel Studies, this paper examines the impact of grandparenting on family fertility decision-making from both theoretical and empirical aspects. Theoretical analysis shows that grandparenting partially offsets the time constraints faced by young couples when having children, reduces the cost of childbearing time, and advances the initial childbearing age of young people, thereby contributing to an increase in the fertility rate. Empirical results validate the findings of the theoretical analysis. Compared with families without intergenerational support, those with intergenerational support tend to contain younger women who have given birth on average, and these women tend to have more children. The findings remain robust to various robustness checks, addressing concerns related to endogeneity. Moreover, the effects of grandparenting are more pronounced for women engaged in non-agricultural work, those with a high income, and those with a high education level.
This study contributes to the literature in the following aspects. First, previous studies have mainly focused on the factors affecting the quantity of children. This study recognizes that childbearing age is an important factor that individuals consider while making fertility decisions. By incorporating female childbearing age into the analytical framework, we examine how grandparenting affects women's childbearing age, offering a novel perspective to existing research. Second, the crucial role of the work-family conflict in women's fertility decision-making has often been overlooked. This paper explicitly incorporates the trade-off between a woman's career and childbearing into the theoretical model and subsequently analyzes the role of grandparenting in alleviating this conflict. The model elucidates the mechanisms through which grandparenting affects childbearing age and the number of children, supplementing the previous literature. Third, this paper empirically validates theoretical propositions based on China's household data and provides direct evidence of how grandparenting affects fertility decisions. Detailed exploration of the heterogeneous effects of grandparenting on fertility and childbearing age enriches our understanding of this topic.
This paper has crucial policy implications. First, policymakers should consider the impact of relevant policies on grandparenting when designing measures to improve the fertility rate. Second, addressing the conflict between women's career and childbearing is the key to shaping women's fertility decisions. During the formulation and evaluation of population policies, the role of gender and women's career development should be comprehensively considered to alleviate the work-family conflict, reduce women's childbearing age, and unlock fertility potential. Third, considerable heterogeneity exists in the impact of grandparenting on individuals' fertility decision-making. Therefore, when designing fertility and population policies, the government should adopt different measures for different types of families and adjust those as needed to achieve desired outcomes.