Investment surges are a typical phenomenon during China's current transitional period, as Justin Lin (2007) observes. Investment may systemically lean toward certain industries, due to either market distortions or government interventions. Investment leanings can lead to capital misallocation and excess capacity in some industries. To correct this imbalance, monetary policies have sometimes been successfully applied to de-capacitize these industries. Theoretically, however, monetary policy does not have structural adjustment functions, even when it is non-neutral in the long run. Therefore, explaining the industrial structural adjustment effects of Chinese monetary policy remains a great puzzle.
In this paper, we explain this puzzle from the perspectives of heterogeneous capacity features and property rights differences between enterprises in China. We construct a theoretical model with a dual financial frictions mechanism in the credit market to illustrate the de-capacitizing effects of monetary policy on excess industrial capacity. The dual financial frictions are the collateral constraint on enterprise and the leverage constraint on banks. The monetary policy transmission is marginally distorted by systematic differences in the balance sheet features of excess capacity industries and the property rights differences of enterprises. We find first that the investments of excess capacity enterprises are more strongly repressed under contractionary monetary policies. Second, state-owned enterprises are less affected by contractionary monetary policies, as they possess better collaterals than private enterprises do. Third, quantitative monetary policy tools are more effective than price-based monetary policy tools.
We use macroeconomic aggregate data and A-share listed firm-level panel data from 2006 Q1 to 2017 Q3 to empirically verify the theoretical hypotheses. We find first that monetary policy has a significant de-capacitizing function. Second, the de-capacitizing function of monetary policy is mainly effective for excess capacity private enterprises. Third, quantitative monetary policy tools are more effective than price-based tools. Finally, expansionary and contractionary operations have asymmetric effects. State-owned enterprises are affected only by expansion. Private enterprises are affected by both expansion and contraction, and are more sensitive to contraction.
Our paper theoretically and empirically verifies that monetary policy has long-term industrial structural adjustment functions in China. It can have such functions when financial frictions and distortions prevail in the financial market, and when enterprises are heterogeneous in balance sheet features and in their ability to obtain external financing in the credit market.
Our work contributes to the literature in the following ways. First, we document and explain the long-term structural effects of monetary policy in transitional economies with financial frictions and institutional barriers. This is different from the traditional conclusion of monetary theories and studies regarding developed economies (Clarida and Gertler, 1999; Walsh, 2003). Second, our dynamic stochastic general equilibrium model clarifies the mechanisms of the de-capacitizing functions of monetary policy, identifying an interest rate channel and a credit channel. These channels fill the mechanism analysis gap in related literature on the de-capacitizing functions of monetary policy (Wei, 1993; Song, 1997; Zhou, 2004). Third, we discuss the effectiveness of interest rate tools and quantitative tools such as reserve requirements. Our paper therefore sheds light on the greater effectiveness of quantitatively based monetary policy tools in addressing structural problems.
Our research has important policy implications. First, different monetary policy tools have different structural adjustment effects. This implies that monetary authorities should choose and apply different tools according to their best marginal effects. Second, the structural adjustment functions of regular monetary policy tools should be considered in practice alongside other structural monetary policy tools. This is consistent with the creative application of monetary management identified by the communiqué of the fifth plenary session of the 19th Central Committee of the Communist Party of China. Third, the full functioning of interest rate marketization depends on the deep reform of microstructure financial markets due to microeconomic agents' heterogeneous features (Xu, 2018). Finally, the coordinated promotion of real economy supply-side structural reforms, interest rate marketization reform, and the construction of a high-level socialist market economy system are essential to a sound price-based monetary policy system.

Regulatory arbitrage and opacity of bank assets were important causes of the 2007-2008 global financial crisis. The full disclosure of information reduces the probability of bank bankruptcy and systemic risk. Banks with greater asset transparency are better able to convey solvency information to the outside world, which makes it easier to attract external refinancing. Conversely, the solvency uncertainty caused by asset opacity may lead to banking crises. Macro-prudential regulation, such as bank capital adequacy ratio regulation, has focused on regulating business on balance sheets. In this context, banks are motivated to move business outside their balance sheets to avoid financial regulation and profit from regulatory arbitrage. There are currently few theoretical or empirical studies on the effects of asset transparency and regulatory arbitrage on banks' systemic risk.
This paper addresses the differences between interbank wholesale financing and retail deposits in depositor market supervision. It further addresses the use of wholesale financing (represented by interbank certificates of deposit) for regulatory arbitrage. Unlike traditional assets and liabilities such as deposits and loans, wholesale financing avoids both investor and depositor supervision and regulatory restrictions. This reduces bank asset transparency and makes banks take greater risks,and excessive connectedness.
This paper first introduces the classical bank moral hazard model in relation to the concepts of bank asset transparency and regulatory arbitrage (represented by correlated risk). We further analyze the effects of asset transparency and regulatory arbitrage on banks' systemic risk from the perspective of theoretical modeling. We also undertake empirical analysis of these effects based on our theoretical model. Drawing on the Wind and Bankfocus databases, we use the rolling window, SRISK and MES methods to measure the asset transparency and systemic risk of China's commercial banks. We fully control for bank level characteristics and macroeconomic factors that may affect systemic risk.
We find that regulatory arbitrage and low asset transparency lead to higher systemic risk. In the case of regulatory arbitrage, the correlation of bank risks and the risk externality of “rarely standing or falling alone” reduce the incentive for bank supervision. This results in collective failure and higher systemic risk. Banks no longer rely entirely on the deposit market for refinancing when interbank regulatory arbitrage occurs. The constraint of transparency on bank risk is weakened and the problem of moral hazard is further aggravated. As a lack of asset transparency weakens banks' financing ability in the deposit market, banks become more active in interbank regulatory arbitrage. Banks may opt for more opaque and risky investments. The homogeneity of assets and risk contagion from interbank certificates of deposit make the banking system more vulnerable. Regulatory arbitrage also weakens the effect of capital regulation on banks' systemic risk.
This paper's contributions are as follows. First, we study systemic risk at the bank level. This paper relaxes the independence setting and introduces asset transparency in the case of heterogeneous portfolios (allowing correlation). We also study the influence of asset transparency on banks' systemic risk. This paper therefore enriches research on the relationship between DELR and bank accounting choice and individual/systemic risk. It also details the mechanism of regulatory arbitrage and its coordination with capital regulation. Second, we study the asymmetric responses of systemically important banks to deposit market supervision using correlation and the setting of creditor and debtor banks. This is another way to support research on the distortion of retail deposit markets by “too big to fail” banks. Third, we add to the retail deposit market literature from the perspective of the wholesale funding market and banks' systemic risk. We also fill the gap in research related tobank asset transpavency and wholesale funding such as shadow banking and Internet finance.

Small financial institutions frequently encounter tail risk events such as insolvency and significant decline in asset quality in the post-crisis period. These events challenge the traditional supervisory concept of “too big to fail.” There is currently growing uncertainty in the capital market and increasing economic downward pressure. The Chinese capital market is also undergoing accelerating reform. It is therefore academically and practically important to investigate the intrinsic tie between bank size and tail risk and to explore the determinants of tail risk.
This paper complements and expands the literature with a high level of originality. First, most domestic literature addresses risk contagion between financial institutions. There is little discussion of whether the “too big to fail” theory can be applied under China's actual economic conditions. Second, there is currently little consensus regarding the direction of effect of bank size on tail risk. The literature suggests that the fundamental variables of financial institutions actually play an important role in this relationship (Buch et al., 2019). Research highlights the need to include fundamental variables in the model to evaluate the heterogenous impacts of institution size on risk-taking more efficiently. Third, linear baseline regression models are often used when researching driving factors of tail risk. However, examining the relationships among variables under the traditional linear empirical framework may result in great bias, as indicated by Acemoglu et al. (2015) and De Vita et al. (2018). This bias makes it difficult to identify the risk sources in the financial system. Finally, research is likely to overlook the fact that the economic reform process exhibits an incremental trajectory in China when analyzing the nonlinear interconnectedness among variables. It is therefore more appropriate to discuss the smooth evolution of tail risk in China under the panel smooth transition regression (PSTR) model.
Our sample consists of 44 Chinese listed financial institutions, comprising 11 banks and 33 non-bank institutions. The sample period runs from January 2008 to June 2020. MES is constructed to represent the tail risk level in this paper. All the data come from the Wind database.
Our paper uses the dominance analysis method developed by Israeli (2007) and Givoly et al. (2019) to investigate the contributions of bank size and other fundamental variables to banks' tail risks. We find that bank size is not the only main determinant of bank risk; variables such as the non-performing loan ratio, personal housing loan ratio, and non-interest income ratio are also significant in the model. We next introduce the marginal effect analysis technique and provide strong evidence of the heterogeneous effects of fundamental variables on tail risk conditional on bank size. Using the PSTR model proposed by Cheikh and Zaied (2020) and González et al. (2017), this paper further discusses the nonlinear impact of bank size on tail risk and the roles of other fundamental variables in this relationship. The result indicates that an increase in the size of banks reduces the tail risk of the financial system in a highly nonlinear way. The reduction of tail risk depends on fundamental variables such as franchise value, asset quality, leverage, cost, income structure, and loan portfolio. The conclusions remain consistent and robust even when we extend our sample to 44 financial institutions. We also find that the evolution of tail risk is more volatile in financial institutions than in the banking sector.
Our findings yield three important policy implications. First, the tail risks of small financial institutions deserve stronger supervisory attention and differentiated regulatory responses, especially at the level of cost management. Second, it is more appropriate to deleverage the financial sector gradually than in a rush. Finally, stronger integrated financial supervision is urgently needed to meet the emerging trend of cross mixed operation in the Chinese financial market. This paper thereby enhances insights into how to deepen financial reform and achieve high-quality economic development in China both theoretically and empirically.

Many papers, when constructing indices of China's financial cycle, include indicators of real estate market conditions as components. However, although many researchers believe that China's real estate sector and financial sector are closely related, there has been little research on this dynamic relationship.In this paper, we attempt to fill this gap by studying the dynamic impact of China's financial cycle on the real estate price. We do this in two steps.
First, we construct an index of China's financial cycle that comprises five financial indicators: stock market performance, interest rate, capital flow, leverage, and money supply. We aggregate the five indicators as a simple average.
In the second step, we construct a three-variate vector autoregressive (VAR) model that includes an indicator of real activities, an indicator of real estate price, and our index of China's financial cycles. The VAR model has a few characteristics. First, we allow the regression coefficients to change over time. Second, we allow the size of the economic shocks to vary over time. Third, we use a recursive scheme to identify structural economic shocks. These characteristics are important for the following reasons. First, China's economy is continuously under reform. These reforms could cause structural changes in the dynamic relationship between the real estate and financial sectors, and omitting those structural changes could lead to misleading results. Allowing the coefficients of the VAR to vary over time should capture those structural changes. Second, due to the changing domestic and foreign economic environment, sources of economic uncertainty change over time. As a result, the size of the shocks to our endogenous variables might also change over time. Third, it is well known that simply interpreting the error terms of the reduced-form VAR as economic shocks omits contemporary correlations between endogenous variables, which can lead to misleading conclusions. Therefore, our VAR model is a structural vector autoregressive model with stochastic volatility and time-varying parameters. The variables in the model are entered in the following order: first, the indicator of real activities, second, the indicator of real estate price, and third, our index of China's financial cycle.
We estimate our model using quarterly data from 2004 to 2016. When constructing our index of China's financial cycles, we use the Shanghai stock market index as the indicator of stock market performance. We use the 7-day inter-bank market interest rate to represent interest rates; the ratio of fixed assets financed by credit to total fixed assets investment as the indicator of leverage; the ratio of the capital and financial account balance to GDP as the indicator of capital flow; and the year-on-year M2 growth rate as the indicator of money supply. Our indicator of real activities is the year-on-year GDP growth rate. Our indicator of real estate price is the China Quality-Controlled Housing Price Index.
The results show that the structural economic shocks to China's economy vary in size over time. The volatility of real activities reached its peak in 2009 and then gradually declined. This suggests that China's macroeconomic policies have helped to stabilize economic growth since the global financial crisis. The volatility of the real estate price also demonstrates a declining trend. However, the trend reversed in 2014 and the real estate price volatility increased until 2016. These results suggest that China's real estate market was developing stably. However, uncertainty has increased in recent years(2015-2016). The volatility of our index of financial cycles gradually increases, suggesting that financial risk during the sample period deserves more attention.
The impact of financial cycle on real estate prices has obvious time-varying characteristics. Before 2008, financial market expansion had a stable influence on the promotion of housing prices, but since 2008, the impact has gradually weakened. Similar to financial shocks, the impact of the real economy on housing prices has also gradually decreased since 2008. This shows that regulatory policies have helped to greatly reduce the sensitivity of real estate prices to economic and financial shocks. The finding that the impact of financial cycles on the real estate price has weakened has important policy implications. A finance-led real estate boom is less likely, which means that the transmission from financial expansion to economic growth through the real estate sector has become less effective since 2008; instead, excessive financial risk-taking accumulates systemic risk. Macro-prudential policies regarding the real estate market are necessary.

The smooth operation, transformation, and upgrade of the Chinese economy inevitably requires the comprehensive development of small and micro enterprises (SMEs). However, financing difficulties have severely restricted the growth of SMEs, causing them to resort to informal channels (such as trade credit) to obtain funds. The Fifth Plenary Session of the Nineteenth Central Committee of the Communist Party of China proposed to support the growth and transformation of SMEs into an important cradle of innovation and to improve policy to promote the development of SMEs. Among these efforts, the implementation of “precise drip irrigation” monetary policy is particularly important for the growth of SMEs and will help to further strengthen the function of financial services in the real economy. To encourage commercial banks and other financial institutions to provide more credit to SMEs and unblock the more formal channels (such as bank loans) through which SMEs can obtain financing, the People's Bank of China, China's central bank, began to implement targeted reserve requirement ratio cuts (TRRRCs) in June 2014.
In contrast to traditional “one size fits all” policies, TRRRCs lower the deposit reserve ratio for commercial banks and other financial institutions. This led to new loans to SMEs accounting for more than 50% of all new loans in 2020 in an attempt to incentivize the allocation of credit resources to weak yet important economic sectors such as SMEs. Therefore, TRRRCs are essentially a quantitative easing tool to improve access to finance for SMEs specifically.
While many studies have evaluated the effectiveness of TRRRCs, due to data availability and causal identification strategies, there is scant research evaluating the impact of TRRRCs on SMEs' other financing channels, such as trade credit, which is as important as bank loans for SMEs when obtaining funds. TRRRCs exert a significant influence on loan availability for SMEs whose sales fall below specific cutoffs. We can thus employ a fuzzy regression discontinuity design (RDD) and use the generated variation in loan availability to identify the impact of access to finance on the trade credit of SMEs. We conduct this RDD using the National Equities Exchange and Quotation's (NEEQ) financial disclosures data from the China Stock Market and Accounting Research Database. The results indicate that the demand for trade credit decreased significantly after the availability of loans for SMEs increased in response to TRRRCs. Furthermore, the allocation of bank loans is often consistent with the value discovery function of the bank. Banks can grant credit to high-quality companies and exert a supervisory function. Therefore, TRRRCs mainly improve loan availability for firms with fewer financial constraints and better market performance. The negative impact of loan availability on trade credit mainly exists among high-quality SMEs. The results are robust after choosing a different bandwidth, controlling for firm characteristics, sharpening the RDD, and excluding other sources of policy interference.
The contributions of this study are as follows. To the best of our knowledge, this is the first study to evaluate the effect of TRRRCs on SMEs' financing decisions. Moreover, the decision to obtain bank loans and trade credit for corporate financing is generally determined by various factors, and this may generate an endogeneity problem. By policy design, TRRRCs only target SMEs whose sales fall below a threshold. If the policy indeed changes loan availability, two kinds of firms whose sales are on the opposite side of the threshold but are otherwise similar will have different levels of financial access. Under this condition, we can use RDD to identify the impact of access to finance on trade credit. The results provide evidence that the substitution relationship between bank loans and trade credit dominates China's SMEs, which enriches the literature on the impact of monetary policy on corporate financing.
This study has clear policy implications. First, since TRRRCs improve SMEs' loan availability, this policy could be employed to ease the financing constraints on SMEs. Second, our results indicate that SMEs with fewer financial constraints decrease their trade credit due to the substitution of bank loans. Credit rationing leads to formal credit resources flowing into high-quality firms. Thus, policy makers are expected to introduce innovative financial policy tools that directly reach the real economy, in particular to help SMEs with severe financing difficulties.
One limitation of this study is that the sample is composed of firms listed on the NEEQ. However, SMEs are found throughout China. Improvements to China's financial information disclosure regulations and the development of data collection and storage capabilities will allow a more representative sample of the financing decision-making issues facing SMEs to be assessed in future research.

In recent years, how to deal with zombie firms has become a widespread concern in top-level design, academic research and social practice in the context of the new era of economic structural transformation and the comprehensive deepening of reforms. In the process of China's economic transition, some companies have suffered long-term losses, near-zero profits and stagnant production. However, they have been able to survive by relying on large financial subsidies and low-cost bank credit and are commonly referred to as “zombie firms.” The existence of zombie firms not only affects the normal functioning of non-zombie firms and creates a crowding-out effect but also reduces the efficiency of resource allocation in the market, hinders technological progress and ultimately impedes high-quality economic and social development.
Furthermore, as an important foundation of socialism with Chinese characteristics, state-owned enterprises (SOEs) play a key role in the rapid development of the Chinese economy and the realization of strategic goals. However, issues such as “owner's absence” and “inner control” have created a relatively serious zombification problem in some SOEs, restricting their core role in the national economy. Therefore, how to better manage state-owned zombie firms and promote the development of high-quality SOEs has become a key element in the success of the comprehensive deepening of reforms in the new era.
On this basis, this paper studies the influence of non-state shareholders' governance on the de-zombification of SOEs in the context of the comprehensive deepening of mixed ownership reform in the new era. The results show that the participation of non-state shareholders in the high-level governance of SOEs can significantly reduce the number of redundant staff and increase capital intensity, thereby reducing the tendency of SOEs to become zombie firms. This effect is more pronounced when state-owned executives have relatively little influence over business decisions and when the equity structure dimension of governance is weak. By subdividing the indicators identifying zombie firms, this paper finds that the governance of non-state shareholders can reduce the degree of zombification of SOEs and promote their normal operation in terms of limiting the acquisition of low-interest loans and improving their profitability. Ultimately, the production capacity and market value of well-managed SOEs are significantly improved.
The findings of this article show that the governance of non-state shareholders plays a positive role in promoting the de-zombification and development of SOEs, which not only provides a useful supplement to the literature on zombie firms' governance and SOE reform but also helps china better coordinate the core role of SOEs in the new journey of building a modern socialist country. In fact, SOEs play an irreplaceable role in promoting the development and growth of the socialist public economy, safeguarding national economic security and achieving national strategic goals, which are paramount in the new journey toward a modern socialist country. This article explores how to achieve the de-zombification of SOEs without losing control of state-owned shareholders and without losing state-owned assets, which is important for practice and policy.
First, the findings of this article provide a workable solution for zombie firms. The governance of non-state shareholders can promote the development of SOEs to a position of honor in the context of mixed ownership reform.
Second, in the mixed ownership reform process of SOEs, it is difficult to empower non-state shareholders to play a governance role by simply mixing equity. Only by better ensuring that non-state shareholders appoint directors, supervisors and senior executives to participate in the governance of SOEs can these shareholders have sufficient discursive power to mix public and private capital from “quantitative change” to “qualitative change.” Therefore, SOEs at all levels of mixed ownership reform should ensure that these shareholders exercise their due rights.
Third, non-state shareholders face many constraints when playing an active role in governance. Top managers in SOEs often have undue personal influence over the enterprise, greatly weakening the voice of non-state shareholders. Therefore, to strengthen the voice of non-state shareholders, it is important to limit the influence of SOE managers, which will better ensure the effective progress of reform.

The Third Plenary Session of the 18th Central Committee of the Communist Party of China highlighted the necessity of actively developing a mixed ownership economy with the mutual integration of state-owned capital, collective capital, and non-public capital. It also recommended that private capital be allowed to participate in state-owned capital investment projects. The influence of mixed ownership reform on corporate behavior is gaining increasing academic attention. The central question addressed in this paper is whether mixed ownership reform affects state-owned enterprises' financial asset investments.
As state-owned enterprises undergo mixed ownership reform, the entry of non-state-owned shareholders may theoretically affect corporate governance structure and resource endowments. This in turn will affect agency conflict and the financing constraints of state-owned enterprises. First, non-state-owned shareholders have a strong motivation to supervise managers as their capital enters state-owned enterprises due to the profit-seeking nature of non-state-owned capital. This motivation helps to alleviate the lack of supervision in state-owned enterprises. When making decisions in this context, a manager will pay more attention to the long-term development of the enterprise rather than short-term benefits. The manager will make more fixed asset investments, such as investments in innovation. However, fixed asset investments have long cycle characteristics. They are therefore subject to more uncertainty and higher adjustment costs. Fixed asset investments will inevitably cause huge losses if they are interrupted. Corporate managers are thus motivated to use financial assets' reservoir effects to reduce the impact of future uncertainty and adjustment costs on their fixed asset investments.
Second, the proportion of state-owned equity has continued to decline with the entry of non-state-owned capital. The policy burden on state-owned enterprises will also be reduced significantly. This change may weaken the resource effect associated with state-owned equity, which will increase the financing constraints faced by enterprises. Based on the precautionary savings motivation, corporate managers will therefore allocate more financial assets to smooth their enterprises' fixed asset investments. Their goal is to avoid financing constraints that would cause fixed asset investment projects to fall into financial difficulties.
Based on the above analysis, this paper uses panel data on China's listed companies from 2010 to 2017 to examine the impact of mixed ownership reform on state-owned enterprises' financial asset allocation behavior. The paper focuses on the motivations behind state-owned enterprises' financial asset investments during the process of mixed ownership reform. The results show that the entry of non-state-owned shareholders promotes state-owned enterprises' financial asset investments. By testing potential mechanisms, we show that both the governance effect and the strengthening effect of financing constraints caused by the entry of non-state-owned shareholders strengthen state-owned enterprises' precautionary savings motivation. State-owned enterprises will therefore increase their investments in financial assets. The above results suggest that it is not the interest-seeking motivation but the precautionary savings motivation that drives state-owned enterprises' financial asset investments in response to the entry of non-state-owned shareholders.
The paper's main contributions are as follows. First, many studies address the economic consequences of mixed ownership reform, but none examine these consequences from the perspective of financial asset allocation. This paper therefore enriches the literature in this area. Second, the literature mostly addresses the economic consequences of corporate financial asset investment, paying less attention to its driving factors. This paper studies the driving factors of enterprises' financial asset investments after the entry of non-state-owned shareholders, thus providing an effective supplement to the literature. Third, this paper's conclusions suggest that state-owned enterprises' financial asset investments in response to the entry of non-state-owned shareholders are driven not by the interest-seeking motivation but by the precautionary savings motivation. When attempting to unravel the complexities of corporate financial asset investments, we should therefore identify the different motives for corporate financial asset investment and treat these motives differently.

This paper examines the relationship between digital finance and regional technology innovation by analyzing province-level panel data from 2011-2018 in a two-step system generalized method of moments model and a dynamic threshold regression model. First, we construct a benchmark linear regression model to verify the influence of digital finance and its sub-indices on regional technology innovation. Second, we use the dynamic threshold panel model to further explore the potential non-linear relationships. The factors include the perfection level of digital finance, the quality of the institutional environment, and the internal absorptive capacity of technology. We also explore two possible mechanisms for digital finance to promote regional technology innovation: the easing of financing constraints and the upgrading of industrial structure. Finally, we explore the potentially differing roles of digital finance in promoting technology innovation in the spatial and temporal dimensions.
There are three main findings. First, digital finance exerts a significantly positive effect on the level of regional technological innovation by easing financing constraints and upgrading industrial structure. Second, the positive effect of digital finance on regional technological innovation is stronger in regions that have better developed digital finance, better institution quality, or a higher level of human capital. Third, we find significant heterogeneity in the spatial and temporal dimensions regarding the role of digital finance in promoting technology innovation. Specifically, the positive effect of digital finance on regional technology innovation is more pronounced in eastern regions and following reforms that promote the development of digital finance.
We propose the following policy implications based on our empirical findings. First, we should promote the deployment of digital finance in China and the digital reform of traditional financial institutions using financial technology under proper governance to improve digital finance in new technology scenarios. At the same time, we must adhere to the unity of marketization, legalization, and internationalization principles, stabilize the pace of development, fully incorporate financial activities into supervision, ensure the safety and stability of the financial system, and optimize the function and efficiency of financial services in the economy. Second, we should improve the institutional environmental quality, local human capital, and other key supporting factors to promote the role of digital finance. On the one hand, we need to refine the existing intellectual property protection laws and regulatory systems, improve law enforcement efficiency, and establish a multi-level legal publicity system. On the other hand, we should build a diversified talent training model and strengthen the construction of technology innovation teams, and formulate appropriate incentive measures and institutional arrangements based on the development status of different regions to maximize the positive effect of digital finance on regional technology innovation. Finally, we should accelerate the transformation of innovation models, improve the level of regional innovation quality review and the construction of innovation evaluation systems, cautiously prevent the appearance of “false” or “strategic” innovation behaviors, and strengthen the effectiveness of financial support and industrial policies that promote the improvement of regional technology innovation.
Our paper also contributes to the literature in several ways. First, we explore the effect of financial development on regional innovation in a new and extensive digital finance model, and validate two possible mechanisms for how digital finance affects the local innovation. To the best of our knowledge, this is the first paper to test the non-linear effect of financial development on technology innovation, thus providing an important supplement to the literature on financial functions. Second, this paper adopts a comprehensive variety of methods, including a dynamic panel model, instrumental variable method, and dynamic threshold panel model, to explore the linear and non-linear relationships between digital finance and the level of technology innovation; it thereby enriches the literature in terms of research methods in the field of innovation, and fully guarantees the robustness of the results. Third, this paper uses the market value of granted patents as a proxy variable, which effectively measures the level and quality of regional technology innovation, to comprehensively examine the impact of digital financial development on regional technology innovation. Therefore, this paper provides new insights on innovation measures and expands the literature on innovation.

It is critical for managers to make appropriate decisions in dealing with supply chain risks (McKinsey, 2010). The literature suggests that, if a supplier firm and its customers can build a cooperative rather than an arm's length relationship, the communication and cooperation between them will not only mitigate the hold-up problem and operating risk induced by major customers (Bensaou, 1999), but also enhance firm performance and value (Kalwani and Narayandas, 1995; Patatoukas, 2012; Irvine et al., 2016). However, few studies in the accounting and finance literature have explored how to build and maintain a cooperative relationship with customers, especially major customers (Anderson and Dekker, 2009). Several scholars have provided limited empirical evidence on cooperative relationship building from the perspectives of capital structure, accounting policies, and earnings management (Banerjee et al., 2007; Kale and Shahru, 2008; Raman and Shahrur, 2008; Dou et al., 2013).
In the literature on trade credit, most studies have focused on the role of accounts receivable as financing (Love et al., 2007; Giannetti et al., 2011), neglecting its role as a product quality warranty when the supplier firm and its customers are attempting to build a cooperative relationship (Smith, 1987). Because it is challenging to obtain large-sample information on specific products and terms of trade credit, the empirical evidence on the role of accounts receivable as a product quality warranty is not only limited, but also indirect (Long et al., 1993; Klapper et al., 2012; Dass et al., 2015). Considering the potential hold-up problem and operating risk induced by major customers, there is a lack of direct empirical evidence on whether and how supplier firms use accounts receivable as a product quality warranty when building and maintaining a cooperative relationship with major customers. Empirical evidence on this topic would provide insight into integrating supply chains and improving supply chain finance, thus enhancing a country's global economic competitiveness.
Our initial sample consists of all firms listed on China's Shenzhen and Shanghai Stock Exchanges from 2005 to 2015. Our sample period starts in 2005 because this is the first year in which a sizable portion of listed firms started disclosing information about their top five customers. In addition, before 2005, to enhance their transparency in response to investors' demands, publicly listed firms in China began to disclose the names of their top five debtors and the corresponding amounts and age of their accounts receivable. We therefore manually collect the location of each top five customer and each top five debtor and the amount and percentage of sales to them for all listed firms between 2005 and 2015. All financial data, the names of the top five debtors, and the corresponding amounts and age of accounts receivable are from China Stock Market and Accounting Research (CSMAR) and China Center for Economic Research(CCER).
Our results show that, when customer concentration is high, credit terms are more lenient; that is, a larger amount of accounts receivable with a longer maturity is provided to major customers. Further evidence shows that, when the geographic proximity between a supplier firm and its major customers is distant, when the supplier firm is in a competitive industry, and when the supplier firm is located in a region with high level of business environment, the positive relation between customer concentration and lenient credit terms strengthens. Lastly, we find that the more credit that is provided to major customers, the better the supplier firm's performance.
This paper makes two contributions to the literature. First, we contribute to the accounting and finance literature on how to build a cooperative relationship with major customers, because there is limited empirical evidence in the literature from the perspectives of capital structure, accounting policies, and earnings management. Second, using the unique data from disclosed information on Chinese listed firms' top five debtors and top five customers, we provide relatively direct empirical evidence on the role of accounts receivable as a product quality warranty when the supplier firm and its major customers are building and maintaining a cooperative relationship. Because it is challenging to obtain large-sample information on specific products and terms of trade credit, the empirical evidence on the role of accounts receivable as a product quality warranty is not only very limited, but also indirect.

Since 1990, the sharp rise and fall of asset prices has been a major issue in China's stock market. Ren et al. (2019) point out that one important reason for the drastic fluctuation of China's stock market is an investor structure dominated by individual investors. Due to limited information and insufficient rationality in investment decision-making, individual investors blindly follow stock market trends, which aggravates the fluctuation. Some scholars have argued that market information asymmetry and the herding effect caused by stock market participants' irrational activity lead to speculative froth in the stock market. For example, Liu et al. (2014) have found that under severe herding conditions, large irrational fluctuations in stock prices can lead to serious bubbles and financial crises. Tao (2017) finds that the synchronicity of Chinese stock prices is much higher than that of developed stock markets in Western countries, and herding behavior causes stock prices to rise or fall together. Therefore, identifying and analyzing the characteristics of herding behavior in China has practical significance for monitoring the stock market and providing early warning of risk.
Domestic studies mainly use a static model, neglecting the time-varying characteristic of herding behavior. A few studies have discussed the dynamic characteristics of herding behavior in the U.S. market (Bohl et al., 2016), but these conclusions may not be applicable to the Chinese stock market, given its differences from Western stock markets in terms of system and development level. Furthermore, China's stock market has a complex structure, comprising the Shanghai, Shenzhen, Hong Kong, and Taiwan markets. Herding behavior may vary due to the different systems and market environments of different sub-markets. To solve these problems, we use a Markov-Switching CCK model to analyze dynamic herding behavior and cross-herding behavior in China's segmented stock markets within a regime-changing environment.
Our sample was drawn from all of China's segmented stock markets during the 1997-2019 period. The data were collected from the Wind, CSMAR, and DataStream databases. The following findings were obtained based on empirical analysis. The cycle of Chinese stock markets can be divided into two regimes characterized by high volatility and low volatility respectively, and the intensity of the herding effect varies with the transition between regimes. For the Shanghai and Shenzhen stock markets, the herding effect is relatively brief and intense in the high-volatility regime, while in the low-volatility regime, the herding effect is longer but relatively mild. For the Taiwan stock market, the herding effect is found only in the high-volatility regime, and lasts for a short time. For the Hong Kong stock market, the herding effect does not exist in either the low-volatility or high-volatility regime. In addition, the A-share markets herd around the U.S. and Hong Kong markets during the low-volatility regime.
The contributions of this paper are as follows. First, considering the special structure of China's stock market, we discuss the herding effect under different systems and market environments, which provides complementary evidence for the time-varying herding effect of China's segmented stock markets under different regimes. Moreover, we contribute to the literature on financial risk contagion. Based on the perspective of cross-border financial linkage, we extend the basic CCK model to the cross-border financial context. By examining the time-varying characteristics of cross-herding, this paper highlights the herding path of risk contagion between stock markets, thus deepening the understanding of financial risk contagion and financial risk management in an open environment. Second, to obtain more rigorous conclusions, we perform necessary parametric tests in the empirical analysis. This can be regarded as a valid method for performing an availability analysis of a Markov switching CCK model, which provides valuable guidance for scholars to conduct more comprehensive, more scientific and more effective research on such a model.

Innovation is crucial to economic development and provides strategic support for the construction of a modern economic system. The capital market plays a key role in promoting corporate innovation and driving economic growth. The Chinese stock market has been developing for nearly 30 years. Market liquidity is increasing with the vigorous development of a multi-level capital market. In this context, this paper explores how stock liquidity affects the innovation strategies of listed companies.
The theoretical literature observes that stock liquidity may have two opposing effects on enterprise innovation. One stream of the literature asserts that stock liquidity stimulates corporate innovation because higher stock liquidity lowers the transaction cost of voting with one's feet. This lower transaction cost is conducive to the entry and exit of large shareholders and institutional investors. Such shareholders and investors are usually active in collecting private information and monitoring managers and thus effective in alleviating the principal-agent problem. Managers therefore pay more attention to corporate governance and devote more resources to R&D activities that enhance company value. This account can be termed the “incentivizing mechanism” of stock liquidity on innovation.
Another stream of literature points out that stock liquidity may instead inhibit corporate innovation. This can be termed the “pressure mechanism”. The inhibition of innovation occurs for several reasons. First, the volatility of stock prices caused by large-scale trading is smaller with higher liquidity. This makes it easier for malicious buyers to cover up large purchases in the secondary market. Managers need to spend more time and energy monitoring stock market transactions when facing such threats. Second, managers need to boost financial performance and maintain high stock prices to raise the costs of malicious purchases. This often requires the reduction of R&D activities. Finally, higher stock liquidity may attract more short-term speculators and passive institutional investors who neither care about corporate fundamentals nor have the incentive to supervise managerial decision-making. This effect often leads to myopic managerial behavior, which may also reduce innovation.
These theoretical controversies suggest that the problem of how stock liquidity affects innovation is essentially empirical. It is worth noting that the Chinese government has made innovation a national policy in recent years and the capital market pays special attention to the innovativeness of listed companies. Under capital market pressure, companies may resort to increasing marginal invention applications and filing many utility models and design patents so that they may appear to have good development prospects.
Our findings are as follows, empirically based on detailed patent data from Chinese listed companies. First, higher stock liquidity leads to significantly more invention applications but does not lead to more grants that are able to pass substantial review. This signals a decline in application quality. Second, higher stock liquidity leads to a significant increase in low quality utility models and designs in the Chinese patent system. These low-quality patents are shown to have negative effects on profitability, and companies less willing to maintain their legal validity. This finding implies that companies only innovate strategically under capital market pressure. Sub-sample regressions reveal that strategic patenting is particularly pronounced among non-state-owned companies, companies in traditional industries, and companies with low long-term institutional investor holdings.
We do not advocate suppressing market liquidity as a solution to the patent bubble problem. Market supervisors should instead persuade investors to base their investment decisions on listed companies' substantive innovative capabilities so that irrational speculative trading can be reduced. The government could also gradually introduce investors with long-term investment visions and value orientations into the capital market, such as social security pension funds. This would help to stabilize entrepreneurs' expectations and encourage innovation.