The global economy is currently caught in a conflicting scenario of low growth and high inflation characterized by frequent balance of payments adjustments and abnormal cross-border capital flows. The outbreak of COVID-19 in early 2020 generated additional external shocks that have further exposed the global economy to uncertainties and vulnerabilities and prompted monetary authorities to weigh the effectiveness of various capital flow management tools. The state of the global economy also poses a major challenge to central banks' monetary policy implementation.
The relationship between different countries' current account movements and monetary policy adjustments should not be neglected. When significant adjustments are made to the current account, the supply of base money and the trend of inter-bank lending rates also show huge fluctuations, with the trends of changes appearing completely consistent at certain points. However, further research is needed to determine the extent to which current account adjustments and reversals caused by external shocks have influenced different countries monetary policy implementation since the 2008 global financial crisis. In this paper, we examine how the central banks of different countries that are facing external shocks and that adopt different capital flow management tools determine their optimal monetary policies.
This paper builds a DSGE model of a small open economy with current account shocks and compares the heterogeneous effects of negative current account shocks on monetary policy implementation. We also examine the transmission mechanisms of different capital flow management tools when the central bank implements quantitative monetary policy rules, the CPI inflation-based Taylor rule and the PPI inflation-based Taylor rule. We also conduct a welfare analysis. The main conclusions of this paper are as follows. First, we find that negative current account shocks affect the central bank's monetary policy implementation. Second, capital flow management can impede negative current account shocks and using a combination of price-based capital account management tools and the Taylor rule of targeting PPI inflation can cause less welfare losses. Third, we find that while dual negative shocks on the trade and investment earnings sides of the current account have a significant impact on a country's monetary policy implementation, public expectations of current account deterioration have less impact on monetary policy implementation.
The findings of this paper have a number of policy implications. First, central banks should attach great importance to the adjustment and reversal of the current account, monitor external balances, try to distinguish the sources of negative shocks, implement appropriate remedies and make quick policy adjustments. Second, central banks should seek to enhance their credibility and actively guide the public to have consistent expectations to actively reduce the occurrence of inconsistent dynamic rules. Third, the central banks of transition economies should be open to implementing price-based monetary policy rules. The optimal monetary policy should balance price stability with risk mitigation, moderately reduce the attention to the nominal exchange rate, prudently promote the process of capital account opening, and use price-based capital account management tools to reduce the distortion of social welfare. Finally, central banks should implement and improve the two-pillar framework of monetary and macro-prudential policy, and strengthen the collocation and coordination of macro-policies.

As the Central Bank, the People's Bank of China(PBC) has continued to implement measures to maintain stable economic development. Notably, the PBC continues to use the Medium-term Lending Facility (MLF) as an important tool for achieving its monetary policy intentions and to improve firms' expectations, investment prospects and financing structures.
Although a number of studies discuss the impact of the MLF, little research examines how the MLF affects the financialization of enterprises. This paper examines this relationship with the aim of clarifying the role that the MLF plays in preventing enterprises from “being diverted out of the real economy.”
This paper uses manually compiled data on the loans and interest rates provided by the MLF on a case-by-case basis. Based on quarterly data from non-financial listed companies from 2014 to 2021, a panel data analysis is conducted to empirically test the impact of the MLF on corporate financialization. The results show that a moderate reduction in the MLF interest rate significantly reduces the level of financialization of firms. Specifically, moderate decreases in the MLF interest rate are found to lead to moderate declines in bank loan interest rates, thus reducing the financing costs of enterprises, ensuring sufficient mid-term and long-term loans for enterprises, improving the investment level of enterprises and alleviating the phenomenon of being diverted out of the real economy. Further analysis shows that the above effects are more significant for enterprises that make active speculative transactions and have strong financing constraints, a heavy tax burden and low levels of regional financialization. These results suggest that the MLF plays a beneficial role in reducing the financing costs of the real economy and promoting long-term corporate financing and investment. Accordingly, the MLF plays a significant role in restraining the phenomenon of being diverted out of the real economy and promoting steady economic development.
The MLF can also play a positive financing role in injecting low-cost capital into the real economy. This additional low-cost capital effectively reduces the financing costs of enterprises, improves their long-term financing and enhances their investment capacity. To achieve this, the MLF makes full use of the operational characteristics of banks and the transmission mechanism of the credit market. Following the successful implementation of the MLF, the PBC created the Targeted Medium-term Lending Facility (TMLF) to provide clearer lending targets and more favorable interest rates and to prevent private enterprises from being diverted out of the real economy,and the economic impact of the new facility is an important topic for future research.
The MLF has a relatively effective micro-transmission mechanism that matches the economic context and can make full use of the pricing mechanism of banks. As the MLF is also highly policy-oriented, policies can be set to make full use of the market mechanism to restrain enterprises from being diverted out of the real economy. As policy can be used to stabilize market expectations, combined with the reform of the loan prime rate mechanism, the MLF’s micro-transmission mechanism enables funds to be precisely targeted in the policy-oriented real economy. The MLF is a major reform initiative and innovation of the PBC. In the future, the MLF is likely to be updated and improved so as to continually optimize its economic impact. Given the increasingly important role the MLF is playing in the monetary policy system, any improvement of the policy is likely to have a positive impact on the real economy. Overall, the MLF is expected to provide increasingly strong and high-quality support for the real economy, improve the stability of the macroeconomic market and contribute to China' new journey toward modernization.

Financial derivatives provide an important means for enterprises to manage their exchange rate risk and are becoming increasingly popular among large enterprises. In recent years, the scale of China's foreign exchange derivatives market has shown a rapid upward trend and consistently maintained a growth rate of more than 20%. In the first half of 2021, the number of companies using foreign exchange derivatives such as forwards and options to manage their exchange rate risk increased by 94% year-on-year. In this context, it is worth exploring the impact of foreign exchange derivatives on the economic behavior of enterprises, as current developments are likely to be of great importance to the future development of China's foreign exchange derivatives market.
Based on information on the use of foreign exchange derivatives provided in the annual reports of A-share listed firms in China from 2001 to 2019, this paper examines the impact of exchange rate risk management behavior on firms' merger and acquisition (M&A) activities. In the process, we explore whether foreign exchange derivatives promote or inhibit the initiation of M&As. We also seek to explain the mechanisms through which exchange derivatives might inhibit M&As.
We find that although listed companies that use foreign exchange derivatives are less likely to initiate M&As than companies that do not use derivatives, the M&A market and the operating performance of companies using derivatives improve. As Chinese listed companies usually pay for M&As in cash using their own funds, the use of foreign exchange derivatives greatly reduces their corporate precautionary cash holdings, and thus reduces their likelihood of initiating M&As. Furthermore, hedging exchange rate risk can reduce company's excessive investment behavior, and thereby improves their investment efficiency. In general, the use of foreign exchange derivatives for exchange rate risk hedging can lead listed companies to pay more attention to the quality of M&As rather than the number of M&As, and thus implement a “less but better” investment strategy.
This paper makes the following contributions to the literature. First, we use text analysis methods to build a unique database on the use of foreign exchange derivatives by companies, and examine how foreign exchange derivatives affect corporate M&As. Second, research on the impact of hedging on companies' investment behavior is mostly based on the cost of corporate debt, and we complement these works by analyzing the impact from a cash holding perspective. Thus, our paper provides a new perspective from which to explain how foreign exchange derivatives affect corporate M&As. Third, as Chinese firms use different payment and financing methods from foreign companies when conducting M&As, the research presented in this paper is adapted to local conditions. Finally, the findings of this paper contrast with the negative impressions that some enterprises have of derivatives and should improve their awareness of exchange rate risk management.
The findings of this paper have a number of policy implications. First, we should accelerate the development of the foreign exchange derivatives market because our findings show that listed companies use foreign exchange derivatives for exchange rate risk hedging rather than speculative purposes. Second, listed companies should optimize their governance mechanisms to avoid conducting inefficient M&As. In particular, our findings show that companies need to prevent large shareholders or management from using excessive cash reserves out of self-interest, which can damage a company's value.
Future studies should collect more accurate data on the use of foreign exchange derivatives by listed companies, such as the intensity of their foreign exchange derivative use. In this paper, we only use the binary dummy variable as the core explanatory variable due to limited data availability. In particular, the data do not reflect the different effects of the use intensity of foreign exchange derivatives on corporate M&As. Second, scholars should use the appropriate instrumental variables for Chinese listed companies to further resolve the endogeneity problems in the empirical model. Finally, M&As are just one way for enterprises to expand, as they can also directly invest in building facilities. Therefore, it is worth exploring how the use of foreign exchange derivatives affects firms' other investment behaviors.

Although China has made remarkable ecological progress in recent years, it still has a long way to go to reach the goal of a carbon peak in 2030 and carbon neutrality in 2060. Given the complexity of the domestic and international economic and social environments, there is an urgent need to resolve the conflict between environmental governance and economic growth. One feasible way to achieve this is to use environmental regulation to promote enterprise green innovation by giving play to the “innovation compensation effect.” As an important component of environmental regulation, green finance policies provide an important means of stimulating the innovation compensation effect. In 2012, the former China Banking Regulatory Commission issued its “Green Credit Guidelines.” By guiding the allocation of credit, this green credit policy is expected to stimulate green innovation among energy-saving and environmental protection enterprises (EEE) and force heavily polluting enterprises (HPE) to engage in more green innovation. However, these effects depend on how banks and enterprises respond to the policy. Thus, this raises the question of whether the green credit policy promotes green innovation and whether the policy effect differs between the two types of enterprises.
Unlike other environmental regulation policies, which only target HPE, the green credit policy also targets EEE. With respect to bank credit decision-making, providing credit support to EEE does not involve environmental risks and can also optimize the bank's credit structure. However, providing credit to HPE does bring environmental risks, which could result in financial and reputational losses for the banks. With respect to the green behavior of enterprises, while the regulatory pressure brought by the green credit policy increases the demand for green innovation among HPE, the credit constraints brought by the policy restrict their capital demand for green innovation. As a result, HPE may choose to engage in low-cost terminal governance and strategic innovation to cope with policy regulation, which will be detrimental to their green innovation. In contrast, the green credit policy aims to promote the development of EEE through credit incentives. As the main business of EEE is to provide green products, green innovation is one of their core competitive drivers. Thus, with the aid of external financial support and the endogenous power of green innovation, EEE are likely to enhance their competitiveness by engaging in increased green innovation.
Taking the Green Credit Guidelines as a quasi-natural experiment, this paper uses the difference-in-differences method to test the different effects of the green credit policy on green innovation by HPE and EEE and their micro mechanisms. We find that the green credit policy has different effects on green innovation by HPE and EEE. Specifically, while the green credit policy can effectively promote green innovation among EEE, it does not provide sufficient support to foster green innovation among HPE. In regard to bank credit decision-making, we find that the different policy effects are partly due to their different effects on credit financing. Specifically, the policy reduces HPE’s credit scale and increases their credit cost, but increases EEE’s credit scale. In regard to enterprise green behavior, we find that the different policy effects are partly due to the different effects on corporate green behavior, such that HPE adopt low-cost strategies while EEE adopt competitive advantage strategies. In addition, the effects of the green credit policy are influenced by the ownership, cash holdings, and size of the enterprises. Bank competition and government subsidies also enhance the effect of the green credit policy in promoting green innovation in HPE.
This paper makes a number of contributions to the literature. First, this paper tests the different effects of the green credit policy on green innovation by EEE and HPE. By identifying the different effects of the policy on the two types of enterprises, our paper provides a more comprehensive evaluation of its effects. Second, we identify the mechanism connecting the macro policy to subject behavior at the micro level based on the transmission chain of the green credit policy. Specifically, based on the credit policy → bank credit decision → green behavior of enterprises → green innovation trajectory, we analyze the micro mechanism of the different effects in relation to bank credit decision-making and enterprise green behavior. These findings shed light on why the green credit policy cannot effectively improve green innovation by HPE. Third, we examine the market-and government-related factors that influence the effect of the green credit policy, and find that a more competitive banking structure and more government subsidies enhance the effect of the green credit policy in promoting green innovation in HPE. This finding provides insight into how the green credit policy can be adjusted to play a more comprehensive role in enhancing green innovation.

In recent years, China's digital economy has grown with the rapid development in emerging technologies. According to the 2021 White Paper on the Development of China's Digital Economy by the China Academy of Information and Communication Technology, the digital economy demonstrated strong resilience despite the global economic downturn caused by the COVID-19 pandemic in 2020 and contributed 38.6% to China's GDP growth. In March 2021, the outline of the 14th Five-Year Plan proposed accelerating the building of a digital economy, digital society and digital government to drive overall changes in production, lifestyle and governance. The digital economy is gathering momentum and is now a part of China's national strategy. In this context, enterprises have wholeheartedly embraced digital transformation, trying to integrate information technology with the traditional modes of production and operation. Academic researchers are also focusing on topics related to the digital transformation of enterprises. Studies have examined the impact of digital transformation on specialization and division of labor, business performance, productivity and input-output efficiency. However, the literature does not discuss the impact of digital transformation on the human capital of an enterprise. Therefore, this study fills a gap in the literature by focusing on this topic.
This study argues that digital transformation relies on the application of intelligent equipment to automate many routine and repetitive tasks through computer programming, which reduces the demand for low-skilled labor in enterprises, and shows the technology substitution effect of digital transformation. In contrast, integration of digital technology with an enterprise's production and operation activities also leads enterprises to deepen their capital. For example, enterprises may purchase more advanced machinery and office automation systems and accordingly improve the level of independent research and development of technology. These changes lead to the creation of many new high-skilled jobs and increase the ability of an enterprise to attract highly skilled manpower. This shows the technology complementarity effect and the scale expansion effect of digital transformation. Therefore, this study investigates whether and how digital transformation affects the upgrading of enterprise human capital.
This study tests the effect of digital transformation on enterprise human capital structure and finds that digital transformation significantly optimizes the human capital structure of enterprises. This conclusion remains valid after accounting for model endogeneity, replacing the core variables, adjusting the model setting and changing the sample size. The mechanism test confirms that digital transformation significantly increases the fixed asset investment and R&D expenditure of an enterprise and its scale of operations. Thus, digital transformation mainly optimizes the human capital structure of enterprises through its technology complementarity and scale expansion effects. The results of heterogeneity analysis demonstrate that the optimization effect of digital transformation on enterprise human capital structure is more prominent in enterprises with less financing constraints and lower technology intensity and enterprises located in the eastern region than in enterprises with more financing constraints and higher technology intensity and enterprises located in other regions. The results of further analyses indicate that digital transformation increases the remuneration of executives and other employees and the operating efficiency of enterprises.
This study makes the following contributions. First, it enriches the literature in the related fields. This study reveals the economic consequences of digital transformation and extends the literature by examining the relationship between AI and labor hiring by enterprises. Second, it provides new empirical evidence indicating how to optimize enterprise human capital structure. This study analyzes how digital transformation optimizes enterprise human capital structure by focusing on the technology substitution, technology complementarity and scale expansion effects of digital transformation. It provides empirical evidence for the change in labor employment structure in a digital economy. Third, the findings of this study have important practical implications. This study shows that digital transformation prompts enterprises to demand more highly skilled labor, and this effect varies according to the characteristics of industries and regions. These findings can provide a practical reference and theoretical basis for the government to formulate more targeted policies for digital economy development.

As a technology-driven financial innovation, financial technology (Fintech) is an important mechanism for deepening the structural reform of the financial supply side and enhancing the ability of the financial sector to serve the real economy. Numerous studies examine the real economic effects of Fintech development. The majority of these studies use the Peking University Digital Financial Inclusion Index to measure Fintech development and analyze its impact on urban income distribution, economic growth, investment, financing and innovation of listed firms and household entrepreneurial activities. The Peking University Digital Financial Inclusion Index, which is compiled by Ant Financial Group, mainly measures the level of non-bank Fintech development. However, studies have yet to examine how non-bank Fintech services that are mainly provided to small and micro enterprises and individuals affect the financing activities of large enterprises. This paper attempts to fill this gap in the literature by exploring the spillover effect of non-bank Fintech development on the financing costs of large enterprises, such as listed companies, and the mechanism of its transmission.
The development of non-bank Fintech can reduce the financing costs of listed companies through the channels of credit competition and information spillover. Compared with traditional financial institutions such as commercial banks, non-bank Fintech companies tend to provide more credit services to small customers. This increase in credit supply reduces the market share that originally belonged to commercial banks. This competitive pressure may prompt commercial banks to increase their risk-taking, lower their credit thresholds or offer more “attractive” loans to maintain their competitive advantages. Thus, large enterprises may have access to more favorable credit services.
However, non-bank Fintech also leads to the generation of more digital transaction records, enhances the capacity of commercial banks to recognize the demand for financial services and reduces information asymmetry in the credit market. The wide application of Fintech also provides new technologies and new methods for commercial bank credit management, and thus reduces moral hazard and operational risk as well as the credit management costs of banks.
Based on financial data from Chinese A-share listed companies, commercial bank data and the Peking University Digital Inclusive Financial Index, this paper explores the effects of non-bank Fintech development on the borrowing costs of listed companies. The empirical results show that for every 10% increase in the level of non-bank Fintech development, corporate borrowing costs decline, on average, by 1.6 percentage points. This effect is more pronounced for smaller firms and firms with poorer financing capabilities, and in areas with higher levels of bank competition. In addition, the development of non-bank Fintech is correlated with a significant reduction in the ratio of non-performing loans and a reduction in the business and administrative expenses of commercial banks. In other words, in addition to increasing competition in the commercial bank credit market, and thereby reducing the cost of corporate borrowing, the development of non-bank Fintech results in information spillover, which can effectively improve the efficiency of bank credit management.
The findings of this paper have a number of policy implications. First, the findings show that the development of non-bank Fintech can help residents and small and micro enterprises obtain financial services and indirectly reduce the financing costs of large firms. Thus, the government should further promote the construction of digital financial infrastructure, as a sound digital financial platform will enable non-bank Fintech to increasingly optimize the supply of financial services.
Second, the digitalization of financial services is an unstoppable trend, and commercial banks should therefore actively embrace digital transformation. Although the development of non-bank Fintech creates competitive pressure, the multi-dimensional information it generates also brings new opportunities for banks. The sooner banks implement digital transformation, the better placed they will be in future market competition.
Finally, enterprises should actively promote digital construction and the accumulation of their own data. Information is an important resource for enterprises as it enables them to better understand their operating conditions. Moreover, Fintech data effectively transmit more dimensional information to the market, thus enabling firms to obtain support from the financial market and conduct better business.

China's rural financial reform has effectively been a top-down storage reform. Before 1990, traditional rural financial institutions (TRIs, including rural credit cooperatives, rural cooperative banks and rural commercial banks) fulfilled a large number of urban construction roles. Following the implementation of China's commercialization and market-oriented reforms, TRIs have preferred to serve urban residents and large and medium-sized enterprises with the goal of making profits. As a result, more financial institutions that originate from rural economies and actively serve rural residents are needed to increase the supply of rural financial services. In 2006, China introduced an innovative reform that encouraged industrial and private capital to invest in new rural financial institutions (NRIs, including village banks, loan companies and rural mutual fund cooperatives). However, the question remains as to whether, under this incremental reform, NRIs are easing financing constraints in rural areas and reducing the urban-rural income gap.
This paper conducts theoretical and empirical studies on NRIs and TRIs. We use the evolutionary game model to examine the results of competition between the two types of rural financial institutions and show, using the income model, that they change the urban-rural income gap by changing the availability of resident loans. In the empirical part, this paper first builds a dynamic panel GMM model using county macroeconomic data and financial institution branch data from 2000 to 2018. The financial institution branch data come from the disclosure of financial license information on the official website of the CBRC, which contains the branch information of more than 200,000 financial institutions in China since 1949 (including address, date of establishment and revocation information). Based on these data, we construct a proportion indicator of rural financial institution branches to explore the different effects of NRIs and TRIs on the income gaps of urban and rural residents. We then use the 2018 China Household Income Survey data (CHIP2018) provided by the China Institute of Income Distribution to build loan availability indexes for urban and rural residents. We use these indexes to test the mediating effects of the loan availability of urban and rural residents on the impact of the increase in rural financial institutions on the income gap.
Our theoretical analysis shows that due to the existence of soft information screening costs and compliance costs, the two types of financial institutions clearly choose to serve customers in different areas. This heterogeneity contributes to the urban-rural income gap, in which the loan availability of residents exerts a mediating effect. Our empirical study also shows that the increase in NRIs has significantly reduced the urban-rural income gap, while the increase in TRIs has widened the gap. Our analysis of the mediating effect shows that the expansion of the two types of rural financial institutions has heterogeneous effects on the loan availability of rural residents and urban residents. Specifically, NRIs improve the loan availability of rural residents, while TRIs reduce it, thus changing the urban-rural income gap.
Overall, our results indicate that the incremental reform of the rural financial market has been more beneficial than the storage reform. However, further reform is needed to reduce the difficulty of market access and strengthen the supervision of the cash flows of NRIs. Moreover, TRIs should be encouraged to increase their investment in microcredit technologies and reduce the difficulty of identifying rural customer risks. Efforts should also be made to enable the human resource advantages of NRIs and the technical advantages of TRIs to jointly serve the rural financial market. According to our proposed new classified supervision model, financial institutions should be able to choose their own regulatory framework and encouraged to build on their strengths and circumvent their weaknesses, and constantly increase their investment in areas where they have comparative advantages. These new institutions, technologies and regulations will help accelerate the establishment of a widely dispersed, multi-level and differentiated banking system in China.
This paper contributes to the literature by exploring the heterogeneous effects of the expansion of two types of rural financial institutions from an intermediate and micro perspective on the evolution of credit constraints and confirming that improving credit constraints has a positive effect on rural residents' incomes. Specifically, we first provide a theoretical basis for formulating policy recommendations by establishing a theoretical model with which to discuss the mechanism of the two types of rural financial institutions in changing the urban-rural income gap by serving different customers. Second, we use county-level data to test the effects of the development of rural financial institutions on changes in loan availability and income. We also reveal more details about the development of NRIs and use micro survey data to confirm the mediating effect of improving credit constraints. Finally, we show that NRIs have better effects in supporting villagers and small businesses. In contrast, as the credit supply of TRIs favors lower risk, TRIs have a better effect on urban residents' credit.

Over-borrowing is a common irrational decision. In recent years, fierce competition in the online loan lending market has lowered the threshold for applying for loans, leading people with low financial literacy to start participating in online borrowing, further exacerbating the phenomenon of over-borrowing.
This article examines a behavioral bias strongly associated with financial literacy—the framing effect. The framing effect can cause the market to have an incentive to manipulate the way information is presented, which implicitly manipulates consumers' decision-making. Therefore, understanding the framing effect in loan decision-making can help policy makers make more specific regulations on the displaying form of loan content and protect the rights and interests of financial consumers more effectively.
This paper uses a laboratory experiment which provides subjects with economically equivalent loan products, and at the same time exogenously change the form of loan costs to study whether the displaying form of loan costs affects loan take-up decisions. Existing literature generally designs loan decisions as intertemporal risk decisions in the laboratory (Giné et al., 2010; Wu Zuguang et al., 2012; Baland et al., 2017). On this basis, we added conditions such as loan cost, consumption value, future income, and overdue fine to simulate the characteristics of consumption loans. This experiment adopts a between-subject experimental design, and the subjects randomly enter into one of Group A (monthly interest amount), Group B (monthly interest rate), and Group C (annual compound interest rate). The information content of the three experimental groups is economically equivalent, and the only difference lies in the displaying form of the "loan cost". Taking the monthly interest rate of 0.5% as an example, Group A sees "the monthly interest rate is 0.5%", Group B sees "the monthly interest amount is 2.5 experimental coins (assuming the loan amount is 500 experimental coins)", Group C sees "the annual compound interest rate is 6.17%".
Holding other variables constant, the loan take-up rate in Group B (monthly interest amount) is 21.30 percentage points higher than that of Group A (monthly interest rate) (which is 21.30/43.42=49.06% higher than that of Group A), and it is statistically significant. Holding other variables constant, the loan take-up rate in group C (annualized compound interest) is 7.91 percentage points lower than Group A (monthly interest rate) on average (which is 7.91/43.42=18.22% lower than that of Group A), and it is also statistically significant.
This paper further explores the channels of the two framing effects and finds that they result from different channels of financial literacy. In a broad sense, financial literacy includes not only people's mastery of financial knowledge, but also people's ability to process economic information and make wise financial decisions (Lusardi and Mitchell, 2014; Liu, 2018). After the loan take-up decisions, we test the financial literacy of the subjects. More than 90% of the subjects correctly answer the questions about the conversion of interest rates and interest amount. We also test the subjects' calculating ability to proxy the heuristics in financial decision-making. Subjects with weaker calculating ability are more prone to the framing effect of interest amount and interest rate. The financial literacy quiz also finds that 71.92% of the subjects have the bias of underestimating exponential growth. The stronger the exponential growth bias, the more prone to the framing effect of single-period interest rate and multi-period compound interest. Therefore, the framing effect of interest amount and interest rates can be explained by the heuristics of financial literacy, while the framing effect of single-period interest rate and multi-period compound interest can be explained by lacking financial knowledge.
This paper proposes a new explanation for over-borrowing in the context of online consumption loan-the framing effect of loan costs, and provides clean and reliable evidence for this using the method of experimental economics. Secondly, this paper divides financial literacy into knowledge and heuristics, and distinguishes the different causes of the two framing effects.
This paper suggests that we need the combination of financial education and financial policy to manage the over-borrowing problem in the Internet age. To alleviate the framing effect of single-period interest rate and multi-period compound interest, government can provide more financial education on the concept of compound interest to the public. To alleviate the framing effect of interest amount in absolute values and interest rate in percentage points, government can directly make clear regulations on the displaying form of loan information, such as adjusting the displaying form of loan costs from single-period interest amount to single-period interest rate, or further adjusting to multi-period compound interest rate.

Commodity markets have become an important part of the modern financial system in China. The trading volumes of commodity futures in the Shanghai Futures Exchange, Dalian Commodity Exchange and Zhengzhou Commodity Exchange rank among the top five in the world. The Chinese commodity futures market is now the second largest in the world, and investors are now more inclined to use commodity futures for hedging and risk management purposes. Commodity futures markets play a crucial role in providing hedging and a price discovery mechanism for investors. The effectiveness of the pricing mechanism affects prices in the commodity spot market and, correspondingly, resource allocation efficiency in the real economy. Therefore, research on the pricing mechanism of commodity futures markets is of great importance for ensuring the stability and vitality of the real economy in China.
Although the pricing mechanism in commodity markets is an important subject of academic research, relatively little research focuses on Chinese commodity markets. Research in this area mainly focuses on the predictive power of macro variables based on traditional economic models. In contrast, the literature on developed markets mainly uses asset pricing factors such as basis, momentum and basis-momentum to explain and predict returns. However, the effectiveness of these pricing factors in China's commodity markets is not adequately studied. Therefore, an appropriate and effective factor pricing model is still needed for Chinese markets.
In this paper, we comprehensively examine the explanation and predictive ability regarding returns of various pricing factors in Chinese commodity futures markets. We find that the basis, momentum and basis-momentum characteristics are important return predictors in Chinese markets. We construct pricing factors and then use the Alpha test, the Gibbons, Ross and Shanken test and an additional empirical test based on the theory of storage to examine the pricing effectiveness of all candidate factor models. Based on our empirical findings, we propose a three-factor pricing model, which includes market, basis and basis-momentum factors. Our paper is the first to provide an in-depth analysis of the pricing mechanism in Chinese commodity futures markets. Furthermore, we provide an intuitive economic explanation for the factors included in the pricing model.
This paper makes the following contributions to the literature. First, in recent years, the pricing mechanism of the commodity futures market has become an increasingly important research topic. In this paper, we conduct a thorough analysis of the effectiveness of basis-momentum, basis and momentum factors, and propose a new factor pricing model for Chinese commodity markets. Our multi-factor pricing model can well explain other factor portfolio returns proposed in the literature, and hence fills the gap in the literature on Chinese commodity markets.
Second, we provide an in-depth explanation of the pricing mechanism for the basis factor based on the theory of storage. We find that the basis factor can effectively explain the returns stemming from the commodity physical inventory status. The basis factor can also serve as a useful proxy for the convenience yield of commodities, which is consistent with the prediction of the theory of storage. Our findings highlight the economic importance and the formation mechanism of the basis factor, and fill a research gap in terms of empirical tests for the theory of storage.
Third, we find that Boons and Prado's (2019) recently proposed basis-momentum factor plays an important role in predicting commodity futures returns in China. These findings thus provide empirical support for the validity of basis-momentum in commodity markets outside the U.S. We also provide an in-depth explanation for the economic intuition of basis-momentum.
Finally, our paper is closely related to the regulatory policies and practices of Chinese commodity futures markets. Regulatory policies on margin requirements and position restrictions are stricter for commodity futures close to maturity. Therefore, investors prefer contracts with longer expiry periods, and these futures contracts have substantially high liquidity. Considering the importance of having sufficient liquidity in commodity futures markets, after conducting a comprehensive comparison of futures contracts of different maturities, we mainly explain the return of the third nearby contract, which is the most actively traded. In general, our paper paves the way for future research on Chinese commodity markets.

The default risk of Chinese firms, which has been increasing since 2014, has attracted significant attention from the government and market participants. Accordingly, reducing default risk is essential for reforming the economy and instigating high-quality development. A number of recent studies focus on the default risk of Chinese firms. These studies examine various determinants of default risk, such as corporate strategies, innovation, financial asset allocation, labor costs and implicit government guarantees. However, few studies examine how free cash flow productivity, a fundamental attribute of firms, affects firm default risk.
In the long run, the criterion for judging the development quality of a firm is whether it can sustainably create value for capital providers. In turn, the ability to create value for capital providers relies on whether the firm can persistently produce cash value added. A high-quality development firm should demonstrate sustainable productivity on cash value added, which first requires the firm to attain persistent free cash flow productivity. Thus, rather than using financing cash inflows to pay capital providers, a high-quality firm should generate operating cash flow above and beyond its investments and the required return to its creditors and shareholders.
We propose that there are three mechanisms by which free cash flow productivity can reduce default risk: first, firms with higher free cash flow productivity are more likely to rely on lower-cost internal financing to cover their investments and less on debt financing; second, firms with higher free cash flow productivity have higher quality assets and higher return on assets; and third, a high level of free cash flow productivity in the long run implies sustainable profitability, which in turn leads to a more transparent information environment and less uncertainty about the value of firm assets.
This paper empirically examines whether free cash flow productivity affects default risk. Specifically, following the literature on free cash flow, this paper measures the free cash flow productivity of firms. Using a sample of A-share listed firms in China, we examine the association between free cash flow productivity and firm default risk, especially when controlling for traditional financial indicators. We find a negative and significant association between free cash flow productivity and firm default risk. Thus, our results suggest that firms with higher free cash flow productivity have lower default risk. This finding is supported by various robustness tests. Moreover, firms with higher free cash flow productivity have lower debt ratios, higher return on assets and lower stock volatility, and thus less default risk. The negative association between free cash flow productivity and default risk mainly arises in periods of monetary policy tightening and in firms with poor external information environments, which partly explains the increase in debt defaults following the tightening of monetary policy in recent years.
This paper makes the following three contributions to the literature. First, this paper contributes to the literature on free cash flow. While studies discuss agency conflict in the use of free cash flow and use free cash flow to measure the agency cost, there is little discussion of the economic significance of free cash flow as a financial indicator from the perspective of free cash flow productivity. Thus, this paper adds to the literature on free cash flow by measuring free cash flow productivity and testing its impact on default risk. Second, from an accounting perspective, this paper complements the literature on corporate default risk by examining the effect of free cash flow productivity as a measure of firm asset quality on default risk. Using the theoretical framework of Merton (1974), the literature focuses on operating cash flow and indirect measures of asset quality, and ignores more multidimensional cash flow information. Using our proposed analytical “five-forces model”, we find that free cash flow productivity can more directly capture fundamental information about asset quality from an accounting perspective, and thus incrementally affect default risk. As a result, this paper extends the literature on default risk. Finally, the findings of this paper have a number of policy implications. In recent years, the default risk of Chinese firms has been increasing and regulators have begun to use free cash flow as a key indicator of the financial management of state-owned enterprises. In this context, our findings can help regulators and stakeholders understand the effects of free cash flow productivity and develop effective measures to encourage listed firms to enhance their free cash flow productivity and, in turn, reduce their debt default risk. Overall, the findings of this paper can help reduce systemic financial risk and contribute to the development of a world-class financial management system.

It is puzzling that based on the same arguments, the literature fails to reach a consensus on the relationship between controlling shareholders' share pledging (CSSP) and firm valuation. Most studies on overseas markets show that share pledging puts margin call pressure on controlling shareholders and induces agency problems between insiders and outside investors. Although numerous studies on the Chinese A-share market show that controlling shareholders have incentives to avoid the risk of forced selling and losing their control rights, they have to work hard, constrain excessive risk-taking and improve the efficiency of risky investments while respecting the interests of investors and creditors.
To address these issues, we build a simple model based on the financing woes of privately owned enterprises (POEs) in both financial access and financing costs. Our model suggests that the relationship between CSSP and firm value is nonlinear and nonmonotonic. The rationale is as follows. Suppose that controlling shareholders have only two financing channels to support their private projects, expropriation and share pledging loans, with trade-offs and substitution effects arising between the two channels. At the early stage, the pledging ratio of controlling shareholders, defined as the proportion of shares pledged by controlling shareholders in their total ownership, is low, and the marginal cost of share pledging is lower than that of expropriation. Thus, at this stage, controlling shareholders prefer to use share pledging loans, and then mitigate the agency problems between controlling (insiders) and minority shareholders (investors), resulting in an increase in firm value. In contrast, as the pledging ratio increases and exceeds some critical levels, the marginal cost of share pledging rises beyond that of expropriation, and the substitution effect then reverses and causes more severe agency problems, leading to falling stock prices. Moreover, the strategic behaviors of controlling shareholders, managers and corporations are influenced accordingly.
Using data on the Chinese A-share market from 2000 to 2020, we empirically evaluate the impacts of CSSP on agency problems and firm value by testing our model predictions. Our regression results show that firm value increases as the pledging ratio of controlling shareholders grows until it reaches about 25%. After this point, the relationship turns negative, and CSSP will harm firm value if controlling shareholders' pledging ratio exceeds 70%. However, due to institutional factors (such as government interference or the shell premium) and strategic behaviors, there exists a tail-raising phenomenon in the relationship between CSSP and firm value, which means that the influence of CSSP on firm value becomes positive again when the pledging ratio hits the ceiling. Furthermore, we find that the market environment works as a moderating variable, implying that the positive relationship between low pledging ratio CSSP and firm value are strong in bull markets, but weak or even the opposite in bear markets.
The main findings of our further analysis are as follows. First, the marginal value of cash declines as controlling shareholders' pledging ratio increases, indicating that CSSP exerts nonlinear effects on firms' governance as the pledging ratio changes. Second, the KZ index and OScore index of pledging firms first fall then rise as controlling shareholders' pledging ratio increases, which is consistent with our model prediction regarding the nonlinearity of the relationship between CSSP and the expropriation incentives of controlling shareholders. This finding also supports the view that CSSP loans are mainly created for personal purposes. Third, the audit fees of pledging firms and their likelihood of committing accounting misstatements/disclosure irregularities increase as the pledging ratio increases, suggesting that firms with high pledging ratio CSSP are more prone to accounting manipulation. Four, most of these findings are not significant in the subsample of state-owned enterprises (SOEs), implying that the motivation of CSSP is different from that of POEs.
Our work makes several contributions to the literature. First, this paper adds to the growing body of research on share pledging. We find a nonlinear and nonmonotonic relationship between CSSP and firm value, in contrast to studies that show the relationship to be either negative or positive. Second, our paper adds to the literature by linking insiders' transactions to their expropriation incentives and then to firm valuation, governance, financing and investment. Unlike studies on external A-share markets, our analysis provides evidence that CSSP can reduce insiders' expropriation incentives when insiders lack access to other financing channels. Third, we complement studies on the relationship between financial slack and agency problems by showing that the marginal value of cash and the probability of firm misconduct are closely associated with the size of the pledging ratio. Finally, our paper adds to the literature on the effects of financial constraints on investment, particularly studies on POEs under China's economic system.