Interest rate is the price of funds and an important variable in the macro-economy. It has great significance for macroeconomic equilibrium and resource allocation. In theory, the natural interest rate equals to the real interest rate when aggregate supply and demand reaches equilibrium. In practice, interest rate directly affects saving and consumption behavior of households, investment and financing decisions of enterprises, as well as import export and balance of payments, and in turn plays an important role in guiding macroeconomic operation. The equilibrium interest rate is determined by market supply and demand, reflecting a combined effect of saving, investment and financing behavior of market entities, such as enterprises, households and financial institutions, in the financial market. In the long run, the interest rate level is supposed to approach the natural interest rate. The central bank should adjust the policy rate to comply with the economic principle, the need of macroeconomic management and cross-cycle policy design. Now China's real interest rate is slightly lower than its economic growth rate and is at a relatively reasonable level. China keeps on promoting the market-based reform of interest rate, which not only adapts to China's actual conditions, but also basically conforms to international practices. While orderly lifting previous restrictions on interest rate, China attaches great importance on the establishment of market-based interest rate system, promoting the critical role of the market interest rate in guiding macroeconomic operation.
China has already established a relatively comprehensive market-based interest rate system. The central bank mainly uses monetary policy tools to adjust liquidity of the banking system, and releases policy rate signals. With the assistance of interest rate corridors, the central bank guides market benchmark interest rate fluctuating around the policy rate, and then transmits to the loan interest rate through the banking system, guiding the supply and demand of funds and the allocation of resources, and achieving monetary policy goals. Recently, the People's Bank of China launched an electronic trading mechanism for the Standing Lending Facility (SLF), to better consolidate the ceiling of the interest rate corridor. In China's market-based interest rate system, some important interest rates may include: the open market operation interest rate as the central bank's short-term policy rate, the medium-term lending facility (MLF) interest rate as the medium-term policy rate, loan prime rate (LPR), reserve interest rate, and Shanghai Interbank Offered Rate (Shibor), etc. In addition, the benchmark deposit rate has played an important role in the past, which has provided an important reference for financial institutions to set their own deposit rates. Now the 1-year benchmark deposit rate in China is 1.5%, financial institutions could either add or minus basis points to the benchmark to set their own deposit rates. This is kind of a "golden-rule level", which meets the need of cross-cycle policy design.
China's yield curve has approached to be mature. In a market-based interest rate system, the benchmark yield curve has great importance, and could provide pricing reference for various financial products and market entities. The yield curve reflects the interest rate term structure from short-term to long-term, and is composed of a series of major market benchmark interest rates. The short end of the yield curve is the overnight and 7-day repo interest rate DR. The central bank could inject base money through open market operations, which directly affect the short-term market benchmark interest rates. The long end of the yield curve is the Treasury bond yield, formed by market transactions, which is mainly based on market expectations of future macroeconomic trends. The investors and policy makers could observe important market information through the Treasury bond yield. A mature yield curve can play an active role in reflecting changes in macroeconomic growth and inflation. In recent years, the compilation and release of China's Treasury bond yield curve has become more mature and the yield curve is widely used. At the same time, the correlation between China and the United States' Treasury bond yields has increased. However, considering the size, turnover rate, and bid-ask spread of the Treasury market, there is still room for improvement in the market basis of China's Treasury bond yield curve compared with the developed markets.
In addition, the asset purchase tool is an operation when the central bank has limited choice during financial crisis. Central banks should avoid implementing the asset purchase tool for too long, for it will cause many problems. If it must be implemented, central banks should adhere to three principles: aiming to help the market back to normal, moving ahead of the market as much as possible, and reducing the scale and duration of asset purchase as much as possible. At present, China has the conditions to implement a normal monetary policy for a longer period, and there is no need to implement asset purchase operation right now.
The People's Bank of China will further deepen the market-based interest rate reform, improve the formation and transmission mechanism of market-based interest rates, promote central bank policy rate system, and strengthen the cultivation of market benchmark interest rates. Meanwhile, the PBC will also continue to strengthen financial regulation, improve business environment, promote hard budget constraints, forestall financial risks, and provide a more favorable condition for further market-based interest rate reform.

The debt to GDP ratio has increased significantly worldwide in the post Covid-19 era, makingmaintaining financial stability a great challenge to regulatory authorities globally. As conventional stress testing models do not consider the contagion of financial risks and thus tend to underestimate the impact of shocks on financial resilience, the central banks in advanced economies have started to develop macroprudential stress test models with specific focus on financial contagion channels. However, studies on the contagion effects within China's banking sector remain very limited. This paper aims to fill this gap and lay the foundation for China's macroprudential stress test framework. Based on the granular balance sheet data of listed Chinese banks, we present a micro-founded model to capture the financial contagion effects within the Chinese banking sector. We focus on the mark-to-market price channel of fire sales, as it is proven to be a critical contagion channel during financial crises. We calibrate the demand curves of multiple asset classes using the bond data, model banks' optimization problems in fire sales with regulatory constraints and simulate the model to exogeneous shocks.
Specifically, we model both the first-round and the second-round effects of financial risks spreading in the banking sector. The first-round effect is the direct impact of a shock on banks, characterized by banks' losses (e.g., credit losses) and the changes in banks' capital adequacy ratios due to the losses. The second-round effect is the financial contagion effect that arises from banks' responses. When a bank breaches its capital requirement due to the initial shock, it has to sell financial assets to boost the capital adequacy ratio. This behavior causes mark-to-market losses of other banks with common asset holdings, which may cause them to breach capital requirements and start another round of fire sale. That depresses asset prices further and generates greater mark-to-market losses. The second-round effect is the contagion channel through which financial risks are amplified and spread in the banking sector.
We also model banks' optimal behaviors in response to shocks. To minimize losses of fire sales, banks consider multiple factors when choosing assets to sell. The first is the risk weight of the assets, as assets with higher risk weights weigh more in calculating capital adequacy ratios. The second is the market depth of the asset. Illiquid assets are typically sold at price discounts which can be quite drastic amid fire sales. Selling illiquid assets leads to greater investment losses and banks need to sell more to meet the capital requirements. The third is the banks' balance sheet structure. Given the price discounts at fire sales, a bank suffers greater losses from selling a class of assets if that asset class accounts for a Large share on the bank's balance sheet.
Our results and policy implications are as follows. First, market depth is critically important in the transmission of contagion risks. As the depth of the Chinese bond market grew from 2017 to 2019, the financial contagion effects were attenuated over the period. In other words, the banking sector in China became more resilient during these three years. Second, individual banks' optimal behaviors may amplify the financial contagion effects. This is because banks all choose to sell the same kind of relatively liquid assets and hence cause sharp price falls of that particular asset, which causes greater mark-to-market losses of other banks holding the common asset. Third, an external shock can generate contagion effects in a non-linear pattern. It is therefore very difficult to discern the emergence and the end of financial risks, which poses a serious challenge for regulators to decide when to act or exit. Forth, it is essential for the regulators to build a macroprudential stress test framework that captures the financial contagion effects. A conventional static bank stress test only captures the direct effects of shocks, and our results suggest that this will greatly underestimate the impact of shocks.
Our paper contributes to the literature in three ways. First, we consider multiple asset classes with different levels of market depth and estimate their demand curve based on the data from the Chinese bond market. That forms the basis upon which we model banks' optimal behaviors in response to shocks. Second, we model banks' optimization problem with regulatory constraint, and analyze the key factors contributing to banks' optimal behaviors. This lays the micro-foundations for stress testing models, which has been omitted in the literature. Third, we investigate quantitatively the effects of financial contagion when banks face the constraint of capital adequacy ratio. The simulation results can help regulators identify the sources of emerging financial risks and assess their impact on the financial system.

Standard money demand models neglect the direct effects of economic openness. This omission is problematic when domestic opportunity cost variables fail to fully reflect the dynamics of international financial markets. Examining the effect of this omission is of great practical importance given the ever-increasing openness of China's economy. We propose composite international financial indices (CIFIs) to measure the latent variables that are omitted in standard money demand models. Using techniques from machine learning and measurement theory, we develop a novel model-based approach to construct CIFIs that combines both unsupervised and supervised dimension reduction methods. The choice of the popular error-correction model for the money demand function leads us to construct two types of CIFIs: long-run and short-run CIFIs.
We collect a large set of around 100 financial input indicators to construct CIFIs using monthly data for the 1993M9-2015M6 period. These input indicators are obtained from 21 economies, covering almost all of China's major trading partners. The CIFI construction algorithm contains two stages of aggregation. First, it produces composite financial input indicators by aggregating groups of financial indicators. These groups are formed using clustering methods under the unsupervised learning approach. Second, it uses supervised dimension reduction methods to aggregate the composite financial input indicators following the principle of partial least-squares (PLS). The algorithm produces short-run CIFIs by targeting money growth rates, whereas it forms the target of long-run CIFIs using the error-correction term of standard money demand models. The second supervised aggregation stage sets the input indicators as leading indicators by construction, allows for dynamic dis-synchronization among them, and performs dynamic backward selection of different lags to make the dynamic input forms of the leading indicators as simple as possible. Concatenation is imposed on the resulting CIFIs during regular data updates.
Experiments with CIFI-enhanced money demand models yield positive outcomes. Our key findings are as follows: (i) We find strong evidence of the effects of foreign opportunity costs on China's money demand based on the statistical significance and constancy of the coefficients of CIFIs and overall comparisons of model explanatory power; (ii) the effect of the short-run CIFIs is particularly robust, as evidenced by the 2007-2008 US-led financial crisis; however, in the enhanced error-correction term of the long-run CIFIs, a temporary coefficient variation toward insignificance is observed, which is interpreted as resulting from the emergency measures taken by the People's Bank of China in response to the crisis; (iii) model performance comparisons of the CIFIs produced with and without the first step of unsupervised dimension reduction show the necessity of this step in that it helps reduce redundant information in large financial datasets; (iv) tracing the compositions of CIFIs back to individual financial input indicators yields various patterns and features that enable the identification of the sources of the aggregate foreign opportunity cost effects.
The explicit links between disaggregate input indicators and aggregate CIFIs provide valuable tools for policymakers to monitor external financial shocks from different geographical regions and markets and assess their aggregate risks in real time. Our CIFI algorithm opens a novel route of model-based composite construction. This route also sheds light on why the conventional route of principal component-based factor analysis is insufficient to construct composite indices for macro-modeling.

With the continuous deterioration of the environment, environment protection and pollution reduction have received worldwide recognition. For China, pollution reduction not only contributes to the construction of ecological civilization, but also helps promote the green transformation of the economy. Besides environmental regulation, support and guidance from the financial sector are also very important for pollution reduction.
From 2007 to 2013, 12 provinces or municipalities in China gradually doubled the SO₂ levy standards from the original 0.63 yuan/kg to 1.26 yuan/kg. Using 2004-2013 China'sEnvironmental Statistios Dataset (CESD) and the sequential adjustments of levy standards as a quasi-natural experiment, this paper applies the difference-in-differences method to examine how the adjustments of levy standards and firms' financing constraints affect firm behaviors and pollution control. Empirical results show that the increase in pollution charge reduces pollution emission by 9.14% while also significantly lowering outputs by 4.43%. The results remain robust in a series of tests. Heterogeneity analysis indicates that large enterprises and state-owned enterprises have carried out effective pollution control, achieving significant reduction in pollution emission intensity without significant drop in outputs. Small and medium-sized enterprises (SMEs) and private enterprises, however, have reduced outputs, and their effect of pollution control needs to be improved. Using credit loan and interest expenditure data, this paper makes further analysis from the perspective of environmental financing. Results show that environmental financing constraints lead to heterogeneous pollution control effects. While implementing the policy, SMEs face substantial environmental financing constraints, which significantly restrains their pollution treatment, aggravates the output adjustment, and ultimately weakens pollution reduction. Controlling for confounding factors (e.g. enterprise size and enterprise pollution emission intensity) that affect enterprise' incentives to reduce pollution does not change the findings.
Enterprises have two options to reduce emission: output reduction and pollution treatment. Pollution treatment usually involves installing pollution disposal equipment, updating production process, and the R&D of green technology which require substantial environmental investment. However, green investments are usually long-term and highly risky with low early return. Relying on internal financing for green investments exerts large pressure on enterprises' cash flows and operational risks. Therefore, when stringent environmental regulations are implemented, there is rising financing demand. If the financial sector ignores this demand, enterprises facing rising emission costs and tight external environmental financing constraints will choose to sacrifice their outputs. This choice not only brings negative economic consequence, but also deviates from the goal of green transformation of production.
The innovation and contribution of this paper are as follows. First, this paper points out that financing constraints affect the outcome of enterprise emission reduction, which enriches the literature on environmental regulation and enterprise pollution reduction, and provides policy enlightenment for the promotion of pollution reduction and the development of green finance. Second, the findings facilitate our understanding of the relationship between environmental regulation and Porter Hypothesis. The literature has long been focusing on whether environmental regulation can stimulate enterprises' green R&D innovation and efficiency improvement. This paper shows that appropriate financial support helps enterprises promote environmental investment. Third, this paper cleans and processes the data of CESD which has not been widely used in academic literature, providing useful experience for applying CESD.
This paper has the following policy suggestions. First, in promoting pollution reduction, we should not only strictly implement environmental regulations, but also pay attention to financial support from the financial sector, so as to improve the pollution treatment capacity of enterprises. Second, to boost environmental investment, the financial sector not only needs to complement the internal weaknesses of China's financial system through ways such as channel funding and reducing borrowing cost for SMEs, but also needs to promote the development of green finance. In providing financial support for enterprise pollution control, uniform environmental risk aversion to polluters is undesirable and enterprises' “green washing” behaviors should be prevented. This requires the financial sector to enhance green finance operations and effectively identify the opportunities and risks in green investment.

Currently, the high-end development of China's manufacturing industry has become a high priority for the country. The development of the manufacturing industry requires efficient cooperation between the producer services industry and the life services industry. Overall, benign coupling and coordination have been achieved between the producer services industry and the manufacturing industry in China. As the real estate industry is an important contributor to the life services industry, the degree of coupling coordination between the real estate industry and the manufacturing industry will directly affect the transformation and upgrading of China's manufacturing industry. The average sale price of commercial housing in 35 large and medium-sized cities in China increased substantially from 2004 to 2016. In the context of the rapid heating of China's real estate market, it is important to judge whether the country's manufacturing industry and real estate industry have achieved coordinated development. This article measures and analyzes the coordinated development of these two industries and thus provides an important reference for formulating policies to promote benign interactions between the two industries.
We manually collect data on 29 subdivided manufacturing industries and the real estate industry in various provinces of China from 2004 to 2016 and measure the degree of coupling coordination between the manufacturing industry and the real estate industry using a coupling coordination degree model. Meanwhile, using the input-output table, we measure and compare the overall driving effects of the manufacturing industry and the real estate industry on each other, identify the best degree of coupling between the two industries from the perspective of the internal mechanism, and use the panel threshold regression method to calculate the value range of the best degree of coupling coordination between the two industries. Furthermore, we examine the impact of the coordinated development of the manufacturing industry and the real estate industry on total factor productivity (TFP) and the economic growth rate through empirical testing. Additionally, considering that during the development of China's real estate industry, China has issued a series of real estate control policies, we use a progressive difference-in-differences (DID) method to analyze the impact of external shocks on the degree of coupling between the two industries.
We obtain five main results. First, the interaction between the manufacturing industry and the real estate industry changed from uncoordinated development in 2004 to coordinated development in 2016. Second, the coordination degree between the two industries in Central and Western China is slightly higher than that in Eastern China. Third, around 2012, the overall development level of the real estate industry exceeded that of the manufacturing industry in Eastern, Central, and Western China. Fourth, in Eastern China, there is a significantly negative relationship between economic performance and the coordination degree between the manufacturing industry and the real estate industry due to the overheated real estate market in this region. Finally, the purchase restriction policy has improved the degree of coupling between the manufacturing industry and the real estate industry. These findings have the following three policy implications: (1) it is necessary to fully consider the driving effects of the manufacturing industry and the real estate industry on each other when formulating industrial policies; (2) it is necessary to strengthen market supervision and create a favorable environment for the healthy development of the manufacturing industry and the real estate industry; and (3) the implementation of purchase restriction policies cannot follow a one-size-fits-all approach as this decreases the positive economic effects of the coordinated development of the manufacturing industry and the real estate industry.
This article makes four contributions to the literature. First, studies often focus on the impact of real estate prices on the manufacturing industry but rarely investigate the coordinated development of the manufacturing industry and the real estate industry, as this article does. Second, this article clarifies the interaction mechanism between the manufacturing industry and the real estate industry. Third, this article gives the best degree of coupling between these two industries from the perspective of the internal mechanism. Fourth, we discuss the impact of the external shock of a real estate purchase restriction policy on the degree of coupling between the two industries.
A possible extension for future research is to compare the coordinated development of the manufacturing and real estate industries in China and developed nations to further investigate the importance of benign interactions between industries for high-quality economic development.

China's economy is entering a new stage of high-quality development, and with the decline of the global demographic dividend and the concurrent release of the regional demographic dividend, the competition between cities for talent and labor forces has gradually become a key focus of the new era. Thus, the study of labor force allocation now focuses on what features are used by cities to attract and retain talent. In China's new urbanization process, people-oriented features are becoming an important part of urban talent attraction and management policies, and urban features that meet consumers' various preferences and personalized needs are gradually becoming an important driver of labor mobility. The production capacity, types, and supply modes of urban services are crucial supports of urban convenience and comfort and provide many ways to improve the welfare of local workers. The increasing demand of cities for labor and the fierce competition between cities to attract talent leads to the following key questions. What role does the diversification and convenience of urban service supply play in labor migration？ What kind of talents are attracted and retained by urban service diversity？ The answers to these questions will have extensive practical significance and implications.
To this end, this study analyzes the effect of urban service diversity on labor mobility from the perspective of comfort and convenience. Thus, an analysis is performed on the data of Meituan, a food-delivery company, and the data from a dynamic monitoring survey of China's floating population in 2017. To deal with the endogeneity problem, the geographical distance between a city and its provincial capital is used as the instrumental variable, and the results confirm that urban service diversity has a significant effect on labor flows. Specifically, a 1% increase in the urban service diversity of a city leads to a 3.23% reduction in the probability that floating population-associated labor will leave that city. That is, if the endogenous problems caused by individual and urban characteristics and missing variables are controlled, a higher diversity of urban services decreases the probability of labor force selection and mobility.
The results of grouping regression based on age nodes and skill levels also reveal that various labor groups have different sensitivities to urban service diversity. For example, the younger population is less likely than the elderly to leave cities with a higher diversity of urban services. In addition, initial analyses show that the mobility and migration probability of the young and middle-aged labor forces decreases by 4.62% for every 1% increase in the urban service category. Furthermore, although the comfort welfare afforded by urban services is important for highly skilled workers and low-skilled workers, highly skilled workers have a greater sensitivity to such comfort welfare.
We also analyze the effect of adjustments in urban and regional environments, and find that the construction of urban informatization technology and the level of marketization have a positive effect on the attraction and retention of talent via their effects on urban service diversity. That is, the construction of information technology (such as urban mobile Internet services) and increased market sophistication attracts labor to live in a city to take advantage of modern products and services, and it therefore reduces the probability of labor mobility or migration. In addition, the results show that labor flow in the central and western regions is less affected by the diversity of urban services than labor flow in the eastern regions. Specifically, the coefficient of the cross terms of age and skill level reveal that labor forces with strong ability or younger age currently prefer to stay in eastern cities. Furthermore, we find that labor flows in big cities are more sensitive to the diversity of urban services than labor flows in small and medium-sized cities, which shows that the comfort welfare represented by the diversity of urban services is an important channel by which large cities draw a population dividend from small and medium-sized cities.
The results of this study have novel implications for the development of policies designed to attract and retain labor force talents, which are part of the urban competition for talent in China. In particular, as the urban economy of China is entering a new stage of high-quality development, the spatial reallocation of labor involves quantitative change in terms of scales of flow and cross-regional migration, as well as qualitative change in terms of the direction of labor structure optimization and efficiency improvements. Moreover, the advantages enjoyed by cities that stem from their ability to attract and retain a high-quality labor force depend on their offering workers a “livelihood channel” of employment and a channel of improved general comfort and welfare. Urban managers and policy designers should therefore make plans based on this reality to cultivate and develop market patterns that are more in line with individual's welfare preferences and thereby to gradually improve the quality of urban labor forces by increasing the diversity of urban service supply systems.

China has developed one of the largest social security systems in the world. However, the proportion of the eligible population that participate in voluntary social programs is far below 100%, which limits the cost-sharing and welfare-protection functions of these programs.
Low rates of participation in voluntary social programs are not a China-specific phenomenon, as they are seen in many other countries (Currie, 2006; Matsaganis et al., 2008). Based on a thorough literature review, Currie (2006) concludes that information friction, stigma costs and transaction costs are the key factors that determine individuals' participation in such programs. However, as acknowledged by Currie (2006), rates of participation in these programs are usually well below 50%, and thus are not wholly attributable to these three factors. Alsan and Yang (2018) and Zhang (2019) show that migration policy and cultural norms, respectively, also affect participation in voluntary social programs. However, these factors only explain the low participation in voluntary social programs with specific policy or cultural backgrounds and are not a general explanation for the low participation in such programs worldwide.
Thus, this paper investigates the role of the peer effect on participation in voluntary social programs, as the peer effect plays an important role in individual decision-making and is an important factor in the uptake of social health insurance (Duflo and Saez, 2002; Liu et al., 2014). We use data from China Family Panel Studies to estimate whether the participation rate of people's neighbors (within the same village) affects people's participation decisions by examining participation in China's New Rural Pension Scheme (NRPS). Our conventional ordinary least squares estimate (OLS) shows that a 1% increase in people's neighbors' participation in the NRPS increases the likelihood of people's own participation by 0.76%, which is significant. We follow Case and Katz (1991) and Duflo and Saez (2002) by using an instrumental variable (IV) approach to detect causal inference. Specifically, we instrument neighbors' participation rates using their average age, which is known to be an important predictor of uptake of social pensions. That is, people's neighbors' age, as demonstrated by Duflo and Saez (2002), can be treated as exogenous when controlling for people's own age. The IV estimate is consistent with the conventional OLS estimate, as it shows that a 1% increase in people's neighbors' participation in the NRPS increases the likelihood of people's own participation by 0.42%, which is significant.
We then explore two mechanisms that may underlie this peer effect: an information transmission-based mechanism and a social norm-based mechanism. To determine if an information transmission-based mechanism exists, we test whether the peer effect decreases as the duration of the NRPS increases. Our OLS and IV estimation results suggest that such a decrease occurs, which supports the existence of an information transmission-based mechanism. We also find that the peer effect is larger if people primarily obtain information from their neighbors, rather than from media such as television and the internet. To determine whether a social norm-based mechanism exists, we measure local clan culture using common surnames and test whether the peer effect is larger in villages containing clans than in villages that do not contain clans. We find that a larger peer effect exists in villages with a stronger clan culture, and as clans are groups with strong cohesion and unified norms, these results support the existence of a social norm-based mechanism.
We also explore whether heterogeneous effects exist by separating the sample according to sex and educational attainment. We find that men have larger effects on their peers than women and therefore probably lead participation in voluntary social programs.
In summary, our findings suggest that the peer effect has a strong influence on people's participation in voluntary social programs, and that the peer effect is driven by information transmission-and social norm-based mechanisms. In addition, we find that the peer effect is asymmetrical: some groups have larger effects on other people's participation decisions than other groups. Our study contributes to the growing literature on the role of the peer effect in individual decision-making, and to the literature on the determinants of participation in voluntary social programs.
The policy implications of our findings are clear. First, enforcing policy advocacy and increasing policy publicity can effectively promote voluntary participation in social programs. Second, using policy interventions to increase the rate of participation of leaders in voluntary social programs effectively increases the overall rate of participation in such programs.

With the development of China's diversified shadow credit market, the non-financial enterprise sector has begun to act as a substantial credit intermediary, becoming the main shadow banking intermediary. The characteristics of shadow banking, such as high leverage, high risk, and information asymmetry, create high uncertainty in the cash flows of the economic entities involved in shadow banking, which intensifies the risk in both the virtual and real economies. Therefore, exploring the economic consequences of the shadow banking activities of non-financial enterprises has important theoretical and practical implications and may help to prevent funds from diverted out of the real economy as well as other systemic financial risks.
Using data of non-financial A-share listed companies from 2006 to 2017, this paper attempts to examine the impact of non-financial enterprises' shadow banking activities on their social responsibility activities, and it further explores the mechanism through which policy continuity affects the interaction between enterprises' shadow banking and social responsibility activities.
This paper's main contributions are as follows. First, it expands the research on non-financial enterprises' shadow banking activities. Second, it enriches the understanding of the effects of policy continuity on micro enterprise behavior and attempts to identify the mechanism through which policy continuity affects the relationship between non-financial enterprises' shadow banking and social responsibility activities. Third, it examines the two channels of relative risk between the finance and entity economies and signal transmission.
The results show that non-financial enterprises' shadow banking activities inhibit social responsibility activities, and this effect is more significant in enterprises with strong market arbitrage motivation, low levels of cooperate governance, and weaker external financing ability. Increased policy continuity weakens the negative relationship between non-financial enterprises' shadow banking and social responsibility activities. The driving mechanisms are as follows. First, increasing policy continuity increases the relative risk of finance investment in the real economy, which weakens the negative effect of non-financial enterprises' shadow banking business on social responsibility activities. Second, an increase in policy continuity enhances the positive information signal that enterprises send to the public through their social responsibility activities.
This paper not only enriches the research on shadow banking, non-financial enterprise financialization, and other academic fields, but also it has important implications for policy makers seeking to improve policy continuity and stability, restrain a shift “from real to virtual” economies, and prevent systemic financial risk agglomeration. Accordingly, this paper puts forward the following policy suggestions. First, strengthen the information disclosure on the financial assets held by non-financial enterprises and enhance the transparency of financial statements. Second, improve the corporate governance structure of non-financial enterprises and strengthen their awareness of corporate social responsibility. Third, enhance the stability and continuity of policies and guide the formation of reasonable expectations. Fourth, continuously promote the structural reform of the financial supply side, optimize the financing structure, strengthen the functional supervision of the shadow banking system, and guide the finance sector to better serve the real economy.

Tremendous increases in scale have been achieved in the development of China's A-share market over the past 30 years. At the end of 2020, there were 4,154 listed companies in the A-share market, and the total value of the market was 80 trillion yuan. This equates to greater than 70% of China's 2020 GDP, meaning that the A-share market is the world's second largest stock market, after that of the United States. However, the frequent abnormal fluctuations that have occurred in the A-share market indicate that the quality of the market is not high.
In particular, there have been continual illegal transactions in the stock market in recent years:China Securities Regulatory Commission reports that the illegal profits from market manipulation in 2020 totaled 416 million yuan. Clearly, such occurrences severely damage the legitimate rights and interests of investors and the healthy development of the capital market. To explore this illegal behavior from the perspective of stock market quality, we monitor and attempt to identify suspicious tail-market manipulation in China's stock market. Based on the results of this monitoring, we empirically analyze how market manipulation affects the information efficiency of China's stock market and suggest ways for regulatory authorities to improve market quality.
Many studies explore the factors influencing information efficiency in the Chinese stock market. Recent studies explore these factors from the perspective of investors and find that institutional investors (Xin et al., 2018), foreign investors (Qinlin and Zhengfei, 2018), and investor sentiment (Yang et al., 2020; Xiong et al., 2020) are responsible for abnormal changes in information efficiency. However, scholars rarely analyze the relationship between market manipulation and information efficiency from the perspective of illegal traders. This is a crucial relationship to understand, as the capital advantage and shareholding advantage of market manipulators means that their manipulations have a profound effect on the formation of stock prices. In addition, market microstructure theory (O’Hara, 1995) holds that the process of formation of security prices is closely related to the type of traders involved. Thus, in the process of stock-price formation, market manipulators may either (i) play the role of informed traders, whereby they use information advantages to bring stock prices closer to their intrinsic values through value investment, which increases information efficiency, or (ii) play the role of uninformed traders, whereby they use capital advantages and shareholding advantages to speculate on stock prices to cause them to deviate from their intrinsic values, which decreases information efficiency. Therefore, it may be unclear how market manipulation affects information efficiency.
Accordingly, in this paper, we explore whether market manipulation is necessarily harmful and the mechanism by which market manipulation affects information efficiency. Specifically, we use the daily high-frequency trading data of the Shanghai A-share market from 2013 to 2018 as a research sample. Then, based on the abnormal characteristics of stock-trading indicators in this sample, we construct a model to identify tail-trading manipulation and empirically test the effect of market manipulation on the information efficiency of stock prices. From these investigations, we obtain the following findings. (1) Market manipulation has an adverse effect on information efficiency, primarily via abnormal changes in stock liquidity and volatility after market manipulation. These findings remain stable after controlling endogeneity. (2) Manipulation has less adverse effects on the information efficiency when the enterprise is state-owend or have a high quality of information disclosure.
Our findings on the adverse effects of market manipulation on information efficiency indicate that financial regulatory authorities should improve market-monitoring and early-warning systems, and increase penalties for violations.

This paper examines the relationship between employee job satisfaction and firm innovation. Theoretically, this relationship is ambiguous. On the one hand, according to stakeholder theory, improved job satisfaction can provide additional compensation and incentives to employees, enhancing their engagement in long-term business activities and reducing their expectation of immediate rewards from short-term activities. Given the high-risk, long-term nature of innovation projects, these effects would be beneficial to firms' innovation and long-term growth. On the other hand, improved job satisfaction may also have a negative impact on firm innovation. Due to agency problems, managers may try to increase employees' job satisfaction by promising high salaries and benefits in exchange for favors. If the increase in job satisfaction reflects the presence of these effects, it should be detrimental to firm innovation. Moreover, programs designed to improve job satisfaction have high costs, which can be deleterious to firm performance if firms consequently invest less in innovative projects. We conduct empirical analyses in this paper to explore the ambiguous relationship between employees' job satisfaction and corporate innovation.
We measure job satisfaction using the “China's 100 Best Employers Award” list. Our full sample consists of 16,876 firm-year observations for firms listed on the Shanghai and Shenzhen stock exchanges between 2011 and 2017. Our baseline results show that the “Top 100” best employers apply for more patents than other listed companies. To eliminate self-selection bias, we use the propensity score matching strategy (PSM) to find a group of non-“Top 100” firms with characteristics similar to the “Top 100” firms. We find that in the PSM sample, the “Top 100” firms apply for about 47% more patents than the matched firms. In addition, we find that job satisfaction mainly improves “Top 100” firms' innovative patents and patents for utility models. Further tests show that job satisfaction mainly improves firm innovation by increasing firms' tolerance of failure. Last, we provide evidence that job satisfaction has a significantly positive effect on firms' innovation efficiency and total factor productivity.
Our paper contributes to several stands of the literature. First, we contribute to research on the labor force and innovation. Most studies explore the impact of employees' stock ownership, the employee-manager pay gap, and employees' income tax on corporate innovation. In this paper, we examine how employees' job satisfaction affects firm innovation by using inclusion in the “China's 100 Best Employers” list as a measurement of job satisfaction.
Second, most studies mainly discuss the impact of labor protection on firm behavior from the perspective of stakeholder protection. Although policy changes can enhance labor protection through legislation, firms' willingness to treat employees well may not increase simultaneously. Consequently, employees' job satisfaction may not change significantly. Unlike studies that focus on the effects of labor protection, we examine how employees' perceptions of firms' incentive system, culture, training, and organization affect their human capital investment in innovation activities.
Finally, our study has policy implications. At present,people tends to pursue better quality of life and greater job satisfaction. Therefore, the previous high-speed economic growth pattern based on sacrificing employees' welfare may no longer be sustainable. Our study provides empirical evidence for this view. These results indicate that modern enterprises should not only rely on employees' hard work but also pay attention to their multifaceted aspirations and job satisfaction. In this way, firms can better use their human resource potential and improve innovation.

After nearly 30 years of development, China's A-share market has gradually become the second largest capital market in the world. However, the capital market is not stable. The sharp decline in stock price can lead to a major loss of investors' wealth and is not conducive to the healthy and stable development of capital markets. Therefore, reducing the risk of sharp decline in stock price has become a hot topic.
Existing literatures attribute the risk of sharp decline in stock price to managers' self-interested hoarding of bad news from the perspective of agency costs and information asymmetry. Managers' behaviors are mostly viewed within the framework of principal-agent theory and are regarded as homogeneous. However, managers are at the heart of business operations, and their personal characteristics, such as perceptiveness, cognitive ability, and values, significantly influence corporate decisions (Hambrick and Mason, 1984). In modern companies, managerial ability is reflected in managers' efficiency in transforming corporate resources into value, relative to their industry peers (Demerjian et al., 2012). Compared with low-ability managers, high-ability managers can accurately understand technology and industry trends,effectively predict product demand, improve project investment efficiency, organize employees, and reduce the moral hazard caused by information asymmetry. Therefore, managerial ability plays a decisive role in ensuring the realization of business objectives.
We explore how managerial ability affects capital market stability using a sample of China's A-share listed firms from 2007 to 2020. Our main proxy for managerial ability is derived from the DEA-Tobit model developed by Demerjian et al. (2012). According to the literature, we use the negative coefficient of skewness of firm-specific weekly returns and the down-to-up volatility of crash likelihood to measure the risk of sharp decline in stock price. The results indicate that managerial ability is significantly and negatively related to both measures of the risk of sharp decline in stock price, suggesting that managerial ability effectively mitigates stock price crash risk. We find that the effect of managerial ability on the risk of sharp decline in stock price is more pronounced for non-state-owned enterprises, for firms with a lower holding ratio of major shareholders, and for firms with lower levels of marketization.
We also discuss the potential mechanisms by which managerial ability can reduce the risk of sharp decline in stock price. We find that managerial ability results in the reduction of a firm's risk, as measured by performance volatility and litigation. Similarly, we find that managerial ability improves corporate governance, as measured by the management expense ratio, discretionary accruals, and information transparency. These findings provide direct evidence that managerial ability reduces the risk of sharp decline in stock price by decreasing a firm's risk and improving corporate governance.
This study may have several theoretical and practical contributions. From the theoretical perspective, the current literature on the risk of sharp decline in stock price mostly uses the principal-agent framework to analyze the negative impact of managers' self-interested behaviors. We investigate the positive effects of managers from the perspective of managerial ability and find that managerial ability mitigates the risk of sharp decline in stock price. Thus, our results supplement the literature on the factors affecting the risk of sharp decline in stock price. In addition, analyzing corporate behavior from the perspective of managerial heterogeneity has become a hot topic. Compared with demographic factors, such as age, gender, and education, managerial ability is a more comprehensive manifestation of managerial heterogeneity. Our conclusions clarify the importance of managerial ability in business development and enrich the literature on the economic consequences of managerial ability. In terms of practical implications, our findings indicate that the relevant policy makers should take effective measures to stimulate and protect managerial ability.