This paper investigates the dynamic effects of monetary policy shocks on non-financial firms' portfolio choices. Unlike conventional empirical analyses, this paper identifies China's monetary policy shocks using high-frequency identification based on the prices of interest rate derivatives, and it utilizes a local projection-IV method to obtain the dynamic effects of monetary policy shocks on firms' portfolio choices. These methods avoid the literature's key weaknesses of endogeneity and static analysis.
This paper uses the high-frequency identification method. First, we calculate the price surprises of one-year FR007-IRS around monetary policy announcements to obtain original monetary policy shocks. We then isolate the autocorrelation component, the central bank private information component, and the component related to economic expectations from original monetary policy shocks to obtain exogenous monetary policy shocks. Positive values in the series of exogenous monetary policy shocks indicate expansionary monetary policy shocks, and negative values indicate contractionary monetary policy shocks. Exogenous monetary policy shocks address the identification problem when studying the impact of monetary policy and validate the estimate of dynamic effects as the instrument variable in the local projection method.
This paper estimates the dynamic effects of monetary policy shocks based on A-share listed non-financial firms from 2007 to 2019. The results for dynamic effects show that positive monetary policy shocks significantly improve the share of financial assets in total assets and the magnitude of the effect exhibits a rising and then declining trend that peaks one and a half years after the shock's occurrence. Moreover, positive monetary policy shocks significantly decrease firms' ratio of cash to total assets in the short term (within one year) but significantly increase it in the long term. Positive monetary policy shocks lead to an increase in scale of real investments in the short term but a decrease in the long term. The results show that monetary policy shocks produce the hangover effects of promoting firms' financialization and reducing the scale of real investments in the medium and long term. Hangover effects refer to long-lasting effects of macroeconomic policies inconsistent with policy objectives. The hangover effects of monetary policy shocks identified in this paper reveal the complex effects of monetary policy adjustments.
Mechanism analysis shows that firms tend to reduce their ratio of cash to total assets and to invest in non-cash financial assets and real assets in the short term because positive monetary policy shocks make both real investments and financial investments more profitable. In the medium and long term, firms save more cash and non-cash financial assets and reduce real investments once the effects of monetary policy shocks (raising returns on real investments and financial investments) have dissipated. These results illustrate that the surplus effects dominate firms' long-term financialization after positive monetary policy shocks occur. Mechanism analysis also rejects competing explanations by showing that neither substitution effects, the irreversibility of financial assets, nor financial investment adjustment frictions explain the propensity of firms to make medium-and long-term financial investments after the occurrence of positive monetary policy shocks and enhances the credibility of the explanation of surplus effects by demonstrating a reduction in firms' accounts receivable and accounts payable after positive monetary policy shocks.
Group-division analysis shows that the hangover effects of monetary policy shocks are stronger for SOEs, firms located in regions with high financial development, and firms with a high ratio of tangible assets to total assets, indicating that positive monetary policy shocks drive firms with more credit resources to increase the ratio of financial assets to total assets more significantly in the medium and long term. This also supports our explanation of surplus effects on firms' long-term financialization.
We make three contributions to the literature. First, this paper uses a high-frequency identification method and isolation of the information effect to construct China's monetary policy shocks, thus addressing the key weaknesses of the endogenous monetary policy indicators used in previous approaches. Second, this paper proposes the presence of hangover effects in firms' dynamic responses to monetary policy shocks and confirms that these hangover effects occur because of firms' surplus effects. Third, this paper characterizes firms' dynamic response to monetary policy shocks of investing in the short term and restoring financial resources in the medium and long term. It thus gives a comprehensive picture of the mechanism of monetary policy shocks in the short and long term, providing evidence for policy makers on how to balance the short-term and long-lasting effects of monetary policy adjustments.

In recent years, the problem of wage distribution imbalance between workers in China has become serious. The wage level of some enterprises, especially leading enterprises, is very high and is increasing rapidly, whereas that of some other companies remains relatively low. Why the wage level of leading enterprises is so large remains in question. According to the neoclassical theory, as long as labor flows freely, wages tend to be equalized across enterprises and the productivity gap disappears because marginal productivity is strictly equal to wages. Even if leading enterprises have higher productivity at the beginning because of their scale and capital advantages, it may only lead to greater employment and not cause drastic changes in wages. Therefore, many scholars pay little attention to the productivity gap when explaining the wage differences between enterprises.
However, in practice, the productivity advantage of leading enterprises can often be smoothly transferred to wages, known as the wage premium. According to existing explanations, the wage premium mostly stems from employees' human capital, per-capita capital, technical, and resulting per-capita productivity advantages. This paper attempts to explain the following problems from another perspective: in the enterprise scale expansion process, what type of transmission mechanism exists between enterprise productivity, per-capita productivity, and wages, and how does this mechanism evolve？ Wages are an important part of income. Clarifying the above issues is conducive to recognizing the source of the wage gap, which has important research implications.
In the theoretical dimension, this paper aims to explain the impact of productivity on wages in different situations, focusing on the role of market shares as an intermediary variable. By constructing a model of labor supply and demand under incomplete competition, we find with greater market share, it is easier for employers and employees to reach a tacit understanding; the employers reach some form of a secret handshake agreement with employees to pursue employment stability and persuade employees to manipulate the labor supply through association, making them deviate from the optimal wage scale, which is similar to the phenomena of production restriction and price increase in a product market monopoly. Thus, employers and employees successfully internalize the productivity advantage of enterprises into per-capita productivity advantages, preventing its spillover to external workers. Although the proportion of employee segmentation declines with this process, it is far from sufficient to offset the impact of the increase in per-capita productivity, thereby resulting in a wage premium.
In the empirical dimension, we conduct an econometric analysis using the data of listed companies (including most of the leading enterprises in China) from 2012 to 2020 to test the above proposition. We include 4,434 companies from 19 industries in our sample. We choose enterprises with operating incomes above the 90^th percentile of the industry as leading enterprise representatives. We use the FE-IV method for econometric regression. Our results show that the productivity-wage transmission strength of the leading enterprises is only slightly weaker (by approximately 4%) than that of the near-median-value enterprises. In contrast, the per-capita productivity difference is much higher (greater than 40%). Moreover, this advantage does not come from the leading enterprises' higher quality of individual workers. Finally, referring to the method of Blanchard and Summers (1986), we prove that leading enterprises display more obvious signs of secret handshake agreements.
The contributions of this paper can be summarized as follows. First, our findings deepen our understanding of the productivity-wage transmission mechanism. In the past, people were confused about the roles of enterprise productivity in wage determination; they did not deny its practical power, but they could not break from traditional theory. This paper highlights that the labor market structure is the key. If the market is frictional, productivity differences may be transferred to wages. Second, this study reminds us that some of the highly paid employees from leading enterprises do not receive high wages because of personal productivity but may monopolize the labor supply through secret handshake agreements. To better achieve common prosperity, we should not only fight against the product market monopoly but also prevent the unreasonable behavior of internalizing productivity advantages.

In recent years, digital finance has rapidly developed in China, and financial technology has significantly improved the quality and efficiency of financial services by promoting the digital transformation of traditional financial institutions. However, some financial innovation businesses based on internet technology are free from conventional supervision, serving as hidden dangers to financial stability. In such circumstances, the fund source stability is poor, thereby challenging liquidity and risk management, violating the supervision and the self-discipline requirements of market interest rate pricing, and hampering the regional restrictions of local banks.
The launch of JD Finance and Fumin Bank's “Fuminbao” in 2018 marked the beginning of third-party cooperative deposits. The third-party platform displays information on deposit products, using phrases such as “bank deposits, principal and interest guarantee,” “100% compensation within 500,000 yuan”. Third-party cooperative deposits cover several high-yield deposit products, becoming a necessary means for some small-and medium-sized banks to absorb deposits and alleviate their liquidity pressure.
Third-party cooperative deposits are categorized as non-proprietary platforms and are strictly regulated; however, there is a lack of academic research on the associated risks. Owing to the convenience, large customer traffic, and high returns of third-party internet platforms, third-party cooperative deposits have resulted in a surge in liquidity to some banks. It remains unknown whether the rapid expansion of the liability side impacts the allocation and risk of the asset side; theoretically, no consensus has been reached. On the one hand, deposit inflows may incentivize banks to take on more risks by alleviating the liquidity pressure. On the other hand, the nature of flexible deposit withdrawal may impose market constraints and limit risk-taking by banks. Therefore, it is critical to clarify the relationship between third-party cooperative deposits and the asset-side risk-taking of commercial banks. This study provides valuable, in-depth insights into the impact of financial technology on risk management by banks and improves the supervision of internet deposits.
This study collects the data of the 2012-2020 semi-annual and annual reports of China's listed banks. Using the difference-in-differences model and setting the start of the third-party cooperative deposit as 2018, we categorize the banks that cooperate with the third-party platform as the treatment group and the non-cooperative banks as the control group. This study finds that the banks in the treatment group took significantly more risks, as indicated by the expansion of risk-weighted assets and increased credit allocation in high-risk industries. Prior to this, a parallel trend existed between the treatment and control groups. The increased risk-taking commenced after the third-party cooperative deposit business began. Therefore, this paper provides causal evidence that third-party cooperative deposit businesses increase the risk-taking of banks.
Analysis of the underlying mechanism shows that the size of the savings deposits of treatment group banks has increased significantly, shifting the risk-taking behavior of banks toward high-interest loans and high-risk industries. By controlling the average deposit costs of banks and the associated interactions, this study excludes the risk transfer hypothesis, i.e., that increases in the cost of deposits augments risk-taking. In robustness tests, we use propensity score matching to select the control and treatment groups for matching, conduct a placebo experiment using the 2015 data, eliminate the regulated industry sample, and add the interactive variables of the bank's wealth management products. It is noteworthy that these robustness checks do not alter the main results of this study.
This study makes the following contributions. First, it focuses on the new perspective of cooperation between banks and internet deposit platforms, assesses the exogenous shock caused by third-party cooperative deposits, analyzes the effects of liability-side business innovations on the asset side, and enriches the literature related to internet finance, financial technology, and micro banking. Second, the mechanism analysis indicates that the surge in liquidity caused by third-party cooperative deposits is the key to improving banks' risk-taking, which implies that regulatory authorities should strengthen liquidity and internet deposit supervision.

China's economy has made great progress in recent years, and Chinese citizens' average income and wealth have greatly increased. The attendant problem of high savings has attracted the attention of policy makers and scholars. As the main form of digital finance, mobile payment has exerted a profound influence on household financial behaviors through its convenience, rich financial functions, and diverse consumption scenarios, and it has thus promoted the growth of China's economy. In this context, it is useful to study the impact of mobile payment on the Chinese household savings rate.
This paper is structured as follows. The first part describes the importance and marginal contribution of the research topic. The second part reviews the literature on mobile payment and the household savings rate and puts forward the research hypotheses. The third part introduces the data, variables, and model specification. The fourth part presents the analysis of the benchmark results and robustness tests. The fifth part discusses the mechanism. The sixth part further analyzes the channels through which mobile payment plays a role. The seventh part presents the heterogeneity analysis. The eighth part presents the conclusions and policy suggestions.
This paper uses data from two rounds of the China Household Finance Survey (CHFS) in 2017 and 2019 and empirically studies the impact of mobile payment on the household savings rate in China using a two-way fixed effect model. To overcome the endogeneity problems caused by omitted variables and measurement errors, this paper uses the proportion of other households in the same community that use mobile payment as an instrumental variable for estimation.
We find that under the two definitions, the use of mobile payment reduces the household savings rate by 18.95% and 15.86%, respectively, and the main ways in which mobile payment reduces the household savings rate are by easing liquidity and credit constraints and expanding social networks. In addition, mobile payment can significantly reduce the precautionary savings that households make to deal with uncertainties such as health risks, medical risks, unemployment risks, and income risks. Regional heterogeneity analysis shows that mobile payment has a greater impact on western China, fourth-and fifth-tier cities, and rural areas. The heterogeneity analysis of family characteristics shows that mobile payment has a stronger effect on agricultural households, middle-and low-income families, and families with a low education level. These findings also reflect the inclusive benefit of mobile payment.
Based on this research conclusion, we make three policy suggestions. First, China should strengthen its policy support to provide digital technical guidance and training for vulnerable groups, improve the market access mechanism, strengthen users' trust in digital platforms, and expand the use of mobile payment from the demand side. Second, China should invest in science and technology infrastructure in underdeveloped regions and expand the popularity of mobile payment from the supply side. Third, China should encourage mobile payment platforms to innovate financial products and services and constantly improve their online health services and information interaction functions to ease household liquidity constraints and reduce background risks.
Overall, this paper makes the following contributions. First, we systematically study the impact of mobile payment on the Chinese household savings rate at the micro household level, expanding the research on the “high savings puzzle”. Second, from the broad liquidity constraints,narrow liquidity constraints and precautionary savings,we discusses the channels of the mobile paymentfunction. We also use a social network analysis of the mobile payment function, providing evidence for the social interaction of mobile payment. Finally, we explore the regional and household characteristic heterogeneity of the influence of mobile payment on the household savings rate and show that mobile payment plays an inclusive role.
In the future, data at the county level can be used to examine the impact of mobile payment on the household savings rate from a macro perspective. It would also be of practical significance to study the impact of mobile payment on China's economy using an empirical methodology.

Advances in digital technology affect the development process of societie and this has become an important force affecting business patterns, factor allocation, and economic structure. As a national strategy, China is developing its digital economy to promote the deep integration of the digital and real economies.Accordingly, this study mainly assesses the impact of digital finance on the branch network distribution and industrial structure changes of traditional banking institutions. As a type of “creative destruction”, the relationship between digital and traditional finance is both competitive and complementary. Simultaneously, the development of traditional finance requires support from the real economy and inevitably varies along with economic and industrial development. Moreover, the impact of digital finance on the development of traditional finance is inevitably influenced by the above factors.
China's indirect financial system is dominated by banks,and the banking system's layout and industry structure can reveal the changes in traditional finance in the digital economy era to a certain extent. The main concerns of this study are as follows: How does the rapid development of digital finance affect the banking industry？ What kind of banking financial institutions are more affected by digital finance？ What factors regulate the impact of digital finance on banking financial institutions？
This study uses financial license data from the China Banking and Insurance Regulatory Commission, and also uses the Peking University Digital Inclusive Finance Index as a measure of the development of digital finance.This study investigates whether digital finance affects the establishment, change, and exit of local banking financial institutions. We mainly assess whether a significant causal relationship exists between regional digital finance and the growth rate of the number of banking financial institutions. To achieve this goal, we adopt the fixed effects model with panel data. In addition, we adopt identification strategies such as explanatory variables with a lag period and instrumental variable regression to avoid the potential issue of endogeneity. Accordingly, we conduct a battery of robustness checks to ensure that our conclusions are valid.
Our findings show that the development of digital finance significantly slows the expansion of physical financial institution outlets in China's banking industry. Moreover, obvious heterogeneity is observed in the results regarding the impact on different types of banks. The development of digital finance slows the expansion of joint-stock and urban commercial banks and mainly affects their grassroots institutions. Although the development of digital finance accelerates the transformation of cooperative financial institutions in rural areas and the withdrawal of outlets, it does not have a significant impact on big state-owned banks. Furthermore, the impact of digital finance improves with economic development and increased regional financial availability but may decline with the improvement of the market power of incumbent banks.
This paper quantitatively measures the possible impacts of digital finance on the banking industry and clarifies its mechanism of action, which can serve as an important reference for financial policy making. In the future, the accelerated development of digital finance is bound to create greater changes in the industry. At the same time, using microdata, we may be able to further explore the specific impact of digital finance on the performance of individual banks.

Education is important for the accumulation of human capital and the realization of high-quality development. Since the 2008 global financial crisis, to improve the quality of its population, China has used public finance to expand its educational input regardless of the economic growth downturn and the disappearing “demographic bonus.” As an instrument of fiscal policy, education finance can alleviate households' educational burdens. However, the last decade has witnessed the large-scale expansion of the out-school education market, thereby increasing households' education expenditures. Therefore, this study investigates whether the goals of increasing human capital input and alleviating households' educational burdens in circumstances wherein out-school education has rapidly expanded in recent years can be compatibly achieved through education finance in China.
Using the education input-output model framework, this study modifies the traditional variable elasticity of substitution education production function via which in-school and out-school education are distinguished. In this model, two parameters are crucial to the substitution elasticity between governmental and household education inputs: the contribution of in-school education to human capital accumulation and the characteristic differences between in-school and out-school education. It is important to assess in what way and to what extent these two factors affect the substitution elasticity in reality.
To empirically investigate whether the relationship between the governmental and household education inputs is substitutional or complementary, this study assesses how education finance input affected household education input between 2009 and 2017 in China. We match the micro-level household data from CFPS investigations to the macro-level provincial data from China Statistical Yearbooks, China Education Statistical Yearbooks, and China Educational Expenditure Statistical Yearbooks. The sample includes individuals from the pre-primary to undergraduate stages. We find that the governmental and household education inputs were complementary rather than substitutional in our sample. This result also passes several robustness tests.
Based on the benchmark results, we further analyze the reasons why the two education inputs were complementary. First, we find that people tend to opine that, compared with in-school education, out-school education more significantly contributes to the accumulation of human capital. Second, the characteristic difference between in-school and out-school education increases the ratio of out-school education input for households. Heterogeneity analyses reveal that the effects of education finance inputs on household education inputs are greater for individuals in the stages of compulsory education.
The study findings have strong policy implications. For the stages of compulsory education, a “dual alleviation” policy for homework and out-school tutoring burden was implemented in 2021; we expect that this policy will render the governmental and household education inputs less complementary in these stages. To ensure that education finance in China achieves the compatible goals of constructing a high-quality education system and alleviating household educational expenditures, it may be beneficial to reduce the substitution elasticity by regulating the out-school education market and rationally recognizing the contribution of in-school education to the accumulation of human capital.
This paper makes several contributions to the literature focusing on education finance and household education investments. First, this study explores the economic mechanisms underlying how education finance influences household educational investments based on the high-speed expansion of China's out-school education market. Second, based on the education input-output model, this study improves the traditional education production function, emphasizes the importance of substitution elasticity between governmental and household education inputs, and highlights that it is crucial to alleviate the burden of household expenditure while maintaining the growth of education finance. Future studies should investigate whether the in-school input overwhelms the out-school input in terms of the contribution to human capital accumulation and whether education finance can effectively substitute household education input once China's out-school education market is regulated.

Food is the paramount necessity of the people. The Chinese central government considers the agricultural economy extremely important and has always regarded solving its people's food issues as its primary task. A report delivered at the 19th National Congress of the Communist Party of China clearly indicates that “agriculture, countryside, and farmers” are fundamental to the national economy and are the top priorities of Communist Party of China, and that we must accelerate the modernization of agriculture and rural areas.
The development of the agricultural economy is restricted by various factors, with the negative effects of climate risk being undoubtedly the most direct and significant. As global warming continues to intensify and climate risks continue to increase, the economic impact of climate risks is receiving increasing attention. Hence, the assessment of the effects of climate risks on the development of the agricultural economy, especially the differences in the effects of climate risks on the agricultural economy in different regions and the underlying mechanisms, has important theoretical and practical significance. Only by clarifying the heterogeneity and mechanisms of these effects can we devise targeted measures to deal with climate risks, thereby offering important strategies to improve the climate risk assessment and response systems, promote the development of a modern agricultural economy, and ensure the security of the food supply.
We first conduct a theoretical analysis of how climate risks affect the development of the agricultural economy and propose hypotheses for testing based on the agricultural aggregate demand-aggregate supply theory and the neoclassical growth theory. Overall, climate risks and the associated natural disasters can cause losses in agricultural produce and increase the marginal costs of agricultural production, thereby shifting the aggregate agricultural supply curve toward the left or upward. According to the aggregate demand-aggregate supply model, the abovementioned changes in the aggregate supply curve may significantly affect the equilibrium of agricultural output in a negative manner. Furthermore, we theoretically analyze why the impact of climate risks on the development of the agricultural economy may differ in regions with different levels of per-capita income, agricultural insurance coverage, and agricultural modernization.
Next, we use the weather station and regional economic data and subject them to the panel fixed-effects model, spatial panel model, and mechanism analysis model to empirically test the above hypotheses. Our empirical results show that climate risks significantly decelerate the growth rate of the agricultural economy. The annual agricultural output growth rate in regions with higher climate risks is approximately 1.05 percentage points lower than that in other regions. Heterogeneity analysis shows that climate risks have a greater impact on regions with lower per-capita income levels. Moreover, climate risks have less impact on regions with higher agricultural insurance coverage levels or higher agricultural modernization levels. This indicates that agricultural insurance can effectively reduce the negative effects of climate risks on the agricultural economy through risk transfer and loss compensation functions, thereby highlighting the importance of financial products in addressing climate risks. Furthermore, improvements in the agricultural modernization levels can effectively reduce the adverse impact of climate risks on the agricultural economy. Finally, mechanism analysis shows that climate risks do not significantly affect agricultural inputs. That is, rather than affecting the output through affecting the input, climate risks directly affect the output. When the severity of natural disasters increases, climate risks directly affect the agricultural economy; moreover, the direct effect is greater than the indirect impact. This indicates that the agricultural insurance coverage, which mainly compensates for the losses caused by direct disasters, is insufficient. Therefore, new products such as agricultural index insurance should be promoted.
Our study makes two major contributions to the literature. First, previous studies assess the economic effects of both natural disasters and climate risks separately; no study provides combined findings for empirical analysis. Because of this disconnect, it is impossible to distinguish between the direct and indirect effects of climate risks on the economy, thereby making it impossible to accurately estimate the economic effects of both climate risk and natural disasters. This paper makes a distinction between the economic effects of climate risk and those of natural disasters, thereby providing a better understanding of how climate risk affects economic development. Second, when discussing the heterogeneity of the impact of climate risks on the agricultural economy, the literature focuses primarily on differences between regions with different incomes and temperature levels. In contrast, our paper examines the heterogeneity from the perspectives of agricultural insurance and agricultural modernization, thereby providing a better understanding of the role of financial markets and agricultural technologies in mitigating climate risk.

China's economy has entered a new era, transforming from high-speed growth to high-quality growth. In this new era, scientific and technological innovations are a matter not only of development but also of survival. The construction of an effective multi-level capital market to enable an innovative and developed real economy is currently an important topic. The establishment of the STAR board and a pilot registration system for high-quality capital market transformation and reforms are warranted to integrate science and technology with the capital market.
The study sample includes all of the enterprises that applied for listing on China's STAR Market from July 2019 to December 2020. The financial data of the samples that went public successfully are obtained from the CSMAR and Wind databases, and the data of the samples that failed to go public are manually collected from their preliminary prospectuses. We construct a high-dimensional enterprise characteristic research index with dozens of factors related to enterprise research and development (R&D), corporate governance, growth, profitability, and risk levels. Based on global stakeholders' perspectives, we explore all of these factors' predictive effects on the listing performance of technology enterprises (e.g., whether to be listed, duration from declaration to listing, amount of funds raised through the listing) and their market performance after listing (stock return and liquidity 3 months after listing and return on assets 1 year after listing). This paper provides comprehensive and direct empirical evidence regarding the practical effects of the incremental reforms of the Science and Technology Innovation Board obtained using the traditional OLS approach and a machine learning dimensionality reduction algorithm.
We use the Boosting regression tree model. The basic idea of this model is that we first set a regression tree from the initial training and then train a new basis regression tree to achieve a loss function that gradually decreases with an increase in iterations. Finally, the weighted regression function is obtained by combining multiple basis regression trees. Moreover, the importance ranking of the enterprise characteristics obtained from the predicted variables is determined based on the training model analysis. Accordingly, using the dimensionality reduction method of principal component analysis, this paper divides the five indexes into several principal components to study the predictive ability of several enterprise characteristics on the financing of science and technology enterprises at two levels. In the first level, we integrate the five segmentation variables into the machine learning model to obtain the R&D, governance, growth, profit, and risk models to study the importance of the various variables within the research groups. In the second level, we integrate the principal components obtained through the dimensionality reduction of the five indexes into the machine learning model to obtain the overall model to study the importance of the various variables without research groups.
Through the methods of OLS and machine learning, this study finds that corporate governance, rather than R&D, is the most important factor in predicting whether an enterprise can be listed on China's STAR Market. R&D investment is the most important of all the R&D variables to predict whether an enterprise can be listed on China's STAR Market. The factors that predict whether an enterprise can be listed on the STAR Market and how an enterprise performs on the secondary market after listing are quite different. The proportion of state-owned shares is more important than the other variables of corporate governance.
The policy implications of these findings are as follows. First, we should balance the attributes of science and innovation with enterprise growth, corporate governance, and other factors. Second, we should consider scientific research personnel important in the development of enterprise innovation. It is necessary to fully support innovation-driven talent. Third, we should pay more attention to the indicators of frontier innovation and establish a multi-angle science and innovation attribute measurement system. Fourth, we should introduce relevant policies to support the sustainable development of enterprises after listing to protect the interests of the majority of investors.
This study makes the following contributions to the literature. First, to the best of our knowledge, this paper is the first to study the factors predicting high-tech enterprises' financing by the STAR board. Few studies report on the financing of high-tech enterprises. Second, this paper uses machine learning to assess the predictive ability of enterprises' multi-dimensional characteristics on financing and adopts the dimensionality reduction algorithm to further study the important relationships between dimensions. Third, the literature on corporate financing focuses on companies' financing motivation to issue stocks or bonds, whereas this study further determines the factors that predict the success of a company's listing on the basis of the company's financing motivation.

Labor is an especially important resource for firms, and it is crucial for the competitiveness of micro enterprises and the development of the macro economy. Therefore, exploring the factors that influence corporate labor investment efficiency is significant in both theory and practice for enhancing the competitive advantage of enterprises and adapting to economic development trends.
The literature examines the factors that influence labor investment efficiency from the perspective of formal systems, such as labor protection, relaxation of short selling constraints, and financial reporting quality, but it neglects the role of informal systems. It is worth noting that formal systems cannot stipulate all operating rules in detail. This suggests the need to investigate the role of informal systems that are internalized in habit and cognition and impose involuntary constraints. As an informal system, trust is a vital form of social capital. However, current research does not explore whether and how social trust affects labor investment efficiency.
Based on a sample of China's A-share listed companies from 2010 to 2018, this paper studies the relation between social trust and labor investment efficiency. The results show that social trust improves corporate labor investment efficiency. Further research demonstrates that the relation between social trust and labor investment efficiency is stronger in firms with severe financial constraints and serious agency conflicts. Moreover, as information asymmetry increases, social trust plays a more significant role in promoting labor investment efficiency. In addition, the effect of improved social trust on corporate labor investment efficiency is mainly manifested in a reduction in under-investment in labor. Social trust can reduce both under-hiring and over-firing of labor.
The main contributions of this paper are as follows. First, by focusing on social trust, the study enriches the literature on the factors influencing corporate labor investment efficiency. Previous studies show that financial reporting quality, conditional conservatism, monitoring of long-term institutional investors, relaxation of short selling constraints, and labor protection are significantly related to corporate labor investment efficiency. However, the literature mainly focuses on formal systems. This paper extends attention to informal systems and discusses the relation between social trust and corporate labor investment efficiency, and thus supplements the existing research.
Second, the study expands the literature on the impact of social trust on micro enterprises from the perspective of corporate labor investment efficiency. Previous research demonstrates the effect of social trust on trade credit, bank loans, risk-taking, mergers and acquisitions, innovation, capital investment efficiency, etc., but neglects labor investment efficiency. There are many differences between labor investment and capital expenditure, and thus the conclusions of previous research concerning the relation between social trust and capital investment efficiency may not be applicable to labor investment efficiency. In addition, labor investment efficiency affects firm performance and macroeconomic growth. This paper relates social trust to labor investment efficiency to obtain a better understanding of how social trust influences the development of micro enterprises and macroeconomic growth.
Third, this paper identifies the mechanisms and specific forms of social trust that can improve corporate labor investment efficiency. The study provides empirical evidence for the mechanisms through which social trust enhances labor investment efficiency from the perspective of financial constraints and agency conflicts. Following prior studies, the paper partitions the sample into subsamples: labor over-investment (over-hiring and under-firing) and labor under-investment (under-hiring and over-firing). It then runs regressions on the subsamples to explore the specific forms of social trust affecting labor investment efficiency. This can not only reveal the underlying mechanisms of social trust influencing labor investment efficiency but also provide insights into the relation between social trust and corporate labor investment.

The negative list for market access is the main channel for relaxing market access. The Third Plenary Session of the 18^th CPC Central Committee proposes to implement a unified negative list system for market access. The term “negative list for market access” is repeatedly emphasized in the Chinese government's important reports and documents, highlighting the significance of the system for maintaining the market order of fair competition and establishing fair, open, and transparent market rules.
The negative list for market access refers to a document that outlines industries and fields that are prohibited or restricted to private investment by companies in China. Industries and fields that are not on the list can be equally accessed by all types of market entities according to the law. This system reduces barriers to market access and attracts more players to enter the market, resulting in competitive effects on the market. Moderate market competition is beneficial. Market efficiency can be improved by exerting competitive pressure on enterprises, reducing agency costs, and extracting enterprise inefficiency. However, excessive market competition can lead to market efficiency loss, which may motivate certain companies to prevent other enterprises from entering the market through preemption and overinvestment; ultimately, this negatively impacts market efficiency. The question here is whether the negative list for market access effectively exploits the market competition mechanism by stimulating market vitality and standardizing government behavior to improve market efficiency. The negative list for market access model is a major upgrade to the negative list governance model used in the domestic economic market. Such a system design is neither used locally nor abroad. Moreover, such a system design has strong theoretical and practical implications in the evaluation of the effects of the negative list for market access on the allocation of market resources.
The direct aim of reforming market access is to improve market efficiency, and at the micro level, corporate investment efficiency is an embodiment of market efficiency. The change from strict to relaxed market access directly affects the corporate investment efficiency. Before the reform, the regulation of market access may prohibit enterprises from entering specific fields or increase the entry barriers for new entrants, resulting in a lack of motivation to improve investment efficiency for those incumbent enterprises. After the reform, many market players seize investment opportunities to enter once-restricted fields. Incumbent enterprises in this field will choose to optimize their investment efficiency or make irrational investments. Accordingly, this study examines the effects of the negative list for market access on corporate investment efficiency to evaluate the micro-level market efficiency of the system.
This paper makes several contributions to the literature. First, theoretically, this study discusses the impact of market access system reforms on enterprise investment efficiency and provides new insights into the economic effects of market access reform. The literature mostly states that market access deregulation affects the business behaviors of micro-enterprises by reducing transaction costs at the market and enterprise levels. Apart from China's unique institutional background and the particularity of the negative list for market access, this paper studies the impact of system reforms to relax market access on enterprise investment efficiency based on competition sufficiency and fairness.
Second, this study tests the policy effects of the negative list system pilot based on corporate investment efficiency and provides empirical evidence supporting the practice of the negative list for market access in China; this system provides solutions for improving the performance of the government's dual functions. The negative list for market access actively guides the expectations and behaviors of market subjects, effectively standardizes governmental behavior, and facilitates the establishment of an effective market and a promising government.

Mutual funds are one of the most attractive investment options for institutional investors in China; thus, understanding the behaviors of mutual funds is crucial for making institutional investments and selecting superior mutual funds. Stock is an important underlying asset for mutual funds, especially equity mutual funds. Furthermore, stock returns are driven by a series of firm characteristics or anomaly factors, and a burgeoning number of factors worldwide provide new investment directions for mutual funds. Institutional investors, including mutual funds, have the motivation and capability to exploit market anomalies. The following questions thereby arise: Do mutual funds exploit market anomalies in Chinese stock markets？ If so, can we select mutual funds based on such exploitation behaviors？
However, the literature mainly focuses on the exploitation of a single market anomaly or single class of market anomalies, and no systematic examination of the hundreds of existing anomalies exists. Moreover, some studies provide contradictory answers to the question of whether institutional investors exploit market anomalies. In addition, most studies are based on the US stock markets, and their findings may not apply to Chinese stock markets. Unfortunately, no such research exists on Chinese capital markets. Thus, this paper seeks to answer the following four research questions: (1) Do Chinese mutual funds exploit stock market anomalies？ (2) If so, can we propose new indicators for mutual fund selection based on their holding stocks and corresponding anomaly factors？ (3) Is the exploitation of stock market anomalies a reflection of fund managers' investment management capabilities？ (4) What are the economic consequences and market impacts of exploiting these anomalies？
To answer these questions, we construct an anomaly score (or A-Score) based on 87 anomaly variables from the Chinese A-share market. To avoid look-ahead bias, we directly adopt the factors from the study by Li et al. (2019). Based on fund holding data and A-Scores of stocks, we further construct the Anomaly Investing Measure (AIM) of mutual funds, which is calculated as the weighted average of holding stocks' A-Score deciles over the whole market universe. A higher AIM indicates that the funds tend to hold stocks with long positions, aggregating the 87 anomaly variables.
Based on actively managed equity mutual funds from 2005 to 2019, we first examine whether mutual funds exploit market anomalies in Chinese stock markets. Our empirical results confirm that funds actively allocate more weight to stocks with high A-Scores as compared with the CSI 300 index and historical holdings and that trading behaviors persist for a long time. Thus, Chinese mutual funds do exploit market anomalies. We next examine the relationship between AIM and the cross-section of mutual fund returns. Results regarding both portfolio sorts and regression show that the AIM significantly predicts future returns; moreover, the AIM can be used to select superior funds. Furthermore, we decompose the fund managers' investment abilities and explore the AIM return sources. The results show that funds with a higher AIM exhibit excellent stock selection, style selection, and risk control ability. Finally, we explore the economic impacts of exploiting anomalies at the fund and market levels. Exploiting anomalies not only ensures long-term fund flows but also alleviates market mispricing.
Our study makes the following contributions to the literature. First, to the best of our knowledge, our paper is the first to systematically examine whether Chinese mutual funds exploit Chinese A-share market anomalies. Contrary to the literature that focuses on a single factor or single class of factors, our paper provides a new perspective on the investment behaviors of Chinese institutional investors by examining 87 market anomalies. Second, based on the stock market anomaly factors, we propose the AIM, which can be used to select superior mutual funds. Our findings enrich the literature on the return prediction of Chinese mutual funds and provide theoretical support for the development of fund-of-funds in China. Third, this paper explores fund managers' investments in stock anomalies from the logic of fund selection of underlying assets and confirms that anomaly exploitation reflects fund managers' superior stock selection, style selection, and risk control abilities. Thus, our study provides a reliable explanation concerning fund managers' investment skills. Fourth, we find that mutual funds' exploitation of market anomalies could reduce arbitrage returns and mitigate mispricing in the Chinese A-share market. Thus, our study enriches the literature on mispricing in the Chinese market and helps understand institutional investors' behaviors from a new perspective.