To effectively promote the high-quality economic development of China's financial sector, the new direction of China's financial reform must include financial structural reform. Indirect financing is the typical financing mode of China's banking system, and thus the banking sector has a key role in financial structural reform in China. In this context, total factor productivity (TFP) is a crucial index for evaluating the performance of financial structural reforms and their ability to generate high-quality economic growth. Therefore, as financial structural reform of China's banking sector is deepening, a method is required to scientifically evaluate and explore the source of the sector's structural TFP growth.
Previous studies typically evaluate TFP growth and decomposition based on technical efficiency. However, technical efficiency examines only the efficiency of individual firms and does not examine the efficiency of an overall sector (or industry). Moreover, the lack of a structural effect may mean that examination of the decomposition of TFP growth could lead to important information on the source of TFP growth being missed. This could include information on structural efficiency change, which involves the improvement of resource reallocation efficiency among individual firms, and information on institutional innovative change, which involves the improvement of the environment of overall banking system. Thus, policy suggestions developed without consideration of the above information could be inappropriate.
To address the above-described research gap, this paper constructs an aggregate Luenberger productivity indicator based on industrial and individual levels of productivity to effectively evaluate and explore the source of structural TFP growth in various banks in China and across China's entire banking sector. First, based on the assumption of variable returns to scale, this paper uses all of the production possibility sets of individual banks to construct an aggregate structural TFP growth model and decomposes this model into overall efficiency change and overall technological change. Overall efficiency change is then decomposed into aggregate technical efficiency change and structural efficiency change, and structural efficiency change is further decomposed into scope efficiency change and scale efficiency change. Additionally, overall technological change is decomposed into aggregate technological change and institutional innovation change.
This paper samples data from 2012 to 2018 from 62 Chinese commercial banks and selects input and output variables according to a profit-oriented approach to evaluate structural TFP growth. To ensure that a reasonable structural TFP growth model is obtained, a direction vector is set using data from 2012 as the base period. This shows that China's banking sector has good structural TFP growth during the study period, with the average annual growth rate being 1.24%. Overall technological progress is found to be the main driver of structural TFP growth, whereas the overall efficiency change has a somewhat negative effect on structural TFP growth. The decompositions of overall technological change and overall efficiency change clearly show that institutional innovation change and aggregate technological progress promote the structural TFP growth of China's banking sector. In addition, all of the components make limited contributions to overall efficiency change. Similar to the findings regarding the effects on China's entire banking sector, it is found that three types of banks perform well: state-owned banks, joint stock banks and local banks. Overall technological change is the main driver of the structural TFP growth of various types of banks, whereas overall efficiency changes have negative effects on structural TFP growth. Furthermore, institutional innovation changes make significant contributions to the structural TFP growth of various types of banks, particularly to that of joint stock banks. Thus, aggregate technological changes have positive effects on the structural TFP growth of joint stock and local banks. In addition, large state-owned banks outperform joint stock and local banks in terms of scope efficiency change and scale efficiency change.
This paper makes the following policy suggestions for financial structural reform based on the results above, which may promote high-quality economic development of China's banking sector. (1) It is imperative that financial structural reform is accelerated, given the current shortcomings in scope efficiency change and scale efficiency change. (2) The strengthening of risk management in China's banking sector must be urgently addressed, as non-performing loans lead to negative technical efficiency change. (3) Full use should be made of financial technology to optimize the structure of banking products, as technological progress is the main driver of the development of China's banking sector. (4) Further improvements must be made to the financial environment and infrastructure, and institutional guarantees and support must be provided to financial services in the real economy because institutional innovation improvement is essential for structural TFP growth.

The Fifth Plenary Session of the Nineteenth Central Committee of the Communist Party of China reveals significant attention to stabilizing the financial system and buttressing the bottom line of systematic risks. Excessive leverage is a potential factor that triggers systemic risks in economic operations, so it is necessary to take a deeper investigation into it. In response to China's rising leverage in recent years, studies have attempted to find its causes from several perspectives, but have yet failed to explain the essential reasons for the formation of leverage resulting from lack of liquidity under the credit currency system. Moreover, the obvious reverse trend between the leverage ratio and the value support of liquidity during 1999 to 2018 has been undervalued by the academia and lacks theoretical explanation.
To this end, this paper constructs a model of preference shocks and liquidity shocks under the credit currency system, deduces the relationship between the value support of liquidity and the formation mechanism of leverage, explains the nature and impact of insufficient liquidity under the credit currency system, and clarifies that the high leverage accompanying insufficient liquidity is caused by the lack of value support of liquidity. Insufficient value support of liquidity depresses economic entity's ability to pay for short-term consumption and stimulates long-term investment. Over-investment brings about the impulse to borrow, thus driving the increase in leverage.
This paper proposes that the value support of liquidity depends on the real value of the currency that can be used for payment when the economic entities need to purchase goods and services. From a national perspective, the currency issued by the central bank is its debt held on behalf of the country, whose value is determined by the debtor's future cash flow (the country's fiscal revenue) and the guarantees provided by the debtor (the reserve assets held by the central bank). In this sense, real liquidity is supported by central bank's reserve assets and government's fiscal revenue. More importantly, the imbalance between the supply and the demand of value support of liquidity can cause the leverage ratio to rise, which may in turn bring about large fluctuations in the economy and even trigger a financial crisis. Therefore, it is necessary to change the motivation and the logic of macro policy implementation. Increasing the number of nominal currencies cannot solve the leverage problem caused by the lack of value support of liquidity. Only by increasing the number of reserve assets corresponding to the issued currency to inject additional value support of liquidity can the liquidity shortage dilemma be solved. Only by solving the constraints imposed by the lack of value support of liquidity on the sustained and healthy economic development can China achieve its strategic goal of accelerating the construction of a new development pattern during the “14th Five-Year Plan” period.
To solve the problem of insufficient value support of liquidity supply, it is essential to re-examine the coordination mechanism of the monetary policy and the fiscal policy under the dual-cycle system. In the domestic big cycle, the problem of excessive investment caused by the shortage of value support of liquidity has affected the smoothness of consumer consumption, which is in conflict with China's goal of boosting domestic demand. To maintain ample value support of liquidity in the whole society, fiscal policies must balance tax rates and maintain reasonable tax revenues. Large-scale and continuous tax cuts cannot be over emphasized. Monetary policy needs to pay attention to both nominal liquidity and the value support of liquidity. In the domestic and international dual cycle, it is necessary to adhere to the concept of openness and expand the scale of international trade. The foreign exchange income from international trade increases central bank's base currency investment through foreign exchange funds and converts into central bank's reserve assets, both of which enhances the value support of liquidity. Since exports are not completely endogenous and there is uncertainty in foreign exchange income, the changes in the monetary base input of the foreign exchange account channel should be closely monitored, and reserve requirements and open market operations should be used timely to hedge its impact. In addition, although the increase in reserve assets can increase the value support of liquidity, there is an optimal scale. Excessive reserve assets will lead to insufficient domestic consumption and cause welfare losses. In this condition, taxes can be reduced appropriately to increase consumption and improve welfare while maintaining a reasonable level of value support of liquidity. In summary, forming a good coordination between the monetary policy and the fiscal policy in the control of the value support of liquidity can stabilize the macro-leverage ratio from the root cause and improve the overall social welfare.

In a long time, China's rapid economic growth was at the cost of pollution, which also has caused serious medical burden of environmental diseases and the loss in health human capital. The phenomenon of “pollution before wealth” restricts sustainable and high-quality economic development. More seriously, we may confront the risk of falling into an “environmental poverty trap”. On Jan 1^st 2018, China implemented environmental tax to guide polluters to reduce emissions, which is of great significance for building a “Beautiful and Healthy China”. Two problems associated with environmental tax are worth exploring. First, it is of theoretical and practical significance to discuss whether environmental tax will realize “double dividend”. Second, confronted with the problems of “pollution before wealth” and “old before wealth”, it is a worthy study whether environmental tax can help to get rid of the “environmental poverty trap”.
This paper constructs an overlapping generation model(OLG), which includes environmental taxes, pollution and life expectancy. The study has shown that environmental taxes have an inverted U-shaped or monotonically increasing relationship with the pollution and per capital income under certain parameters. This relationship indicates that the lower tax rates may increase pollution and excessive tax rates may reduce per capital income. The corresponding mechanism is that while the “negative revenue effect” of environmental taxes leads to a decline in capital accumulation, the “health effects” of environmental taxes increases life expectancy and capital accumulation. The effect of environmental taxes on the environment and the economy is transmitted through capital accumulation. The government has more revenue by increasing tax rates in environment to increase expenditure on environmental governance, which makes it easier for the economy to generate green dividends. Further, we find that there is a certain tax rate interval to achieve a “double dividend”, which is in line with the green development concept of “lucid waters and lush mountains are invaluable assets”. Under the endogenous growth framework, there are multiple equilibrium points, that is, a stable balanced growth path and an environmental poverty trap. On the balanced growth path, the environmental tax rate and economic growth have an inverted U-shaped relationship.
The contributions of this paper are as follows: First, this paper introduces life expectancy with the concept of “prevention is greater than cure” and emphasizes the time lag of pollution and public health on health. This paper enriches the mechanism of environmental taxes on consumption and savings from the perspective of “life cycle” by introducing life expectancy. Second, under the neoclassical growth framework, the existence of “double dividend” provides theoretical foundation for the green development concept. Third, Under the endogenous growth framework, we find that environmental policies can explain the phenomenon that some countries have realized the model of “environmental Kuznitz curve”, while others falled into the “environmental poverty trap”, which enriches the theoretical mechanism for explaining income disparity among countries.
The policy recommendations mainly include following points: There is an optimal environmental tax rate in the economy,that is,an excessively low environmental tax rate may aggravate pollution, and an excessively high environmental tax rate may will inhibit economic growth. Chinese environmental tax only accounted for 0.14% of total tax revenue in 2019, so the environmental tax rate should be appropriately increased. Local governments make a comprehensive consideration of the environmental carrying capacity, pollutant status and economic development goals when formulating differentiated environmental tax rates. We will focus on raising environmental tax rates for industries with high pollution and carbon emissions, and achieve the goal of coordinated pollution reduction and carbon reduction. Second, according to the pollution accumulation equation, pollution depends on investment, emission intensity and governance efficiency. It is necessary to increase investment in environmental governance, reduce pollution emission intensity through upgrading technology and restructuring industrial structure, and improve governance efficiency by updating environmental governance equipment and technology. Third, pollution causes health damage to residents, so the government should increase people's health and consumer welfare caused by pollution through increasing public health spending.

This paper uses the forecast combination method to predict the GDP growth and CPI growth in China. It also compares the out-of-sample performance of predictive model forecasts, expert forecasts, and combined forecasts in predicting GDP and CPI growth, and analyzes forecast errors to explore whether the forecast combination method can improve forecasting accuracy in different economic periods.
We choose several predictive models from multiple perspectives. First, we use the regime-switching model (RSM) to reflect the dynamic patterns of GDP and CPI growth rates during stable and volatile periods. Second, we use the mixed data sampling model (MIDAS) to incorporate the information content of monthly data to improve the accuracy in predicting quarterly macro variables. Third, we use the mixed-frequency error correction model (MF-ECM) to consider the cointegration relationships between variables. To use a multi-dimensional and high-frequency macroeconomic dataset in prediction, we also resort to the mixed-frequency vector autoregression (MF-VAR). In addition, since the growth rates of GDP and CPI are both first-order single integral time series, the autoregressive integrated moving average model (ARIMA) is included as a benchmark.
We use the forecasts of macroeconomic variables in the “Langrun Forecast” program to construct our expert forecast data. We choose the “Langrun Forecast” mainly for two reasons. First, it contains forecasts from various institutions and covers a long time period. Second, the forecasts included are all provided by well-known academic institutions or leading commercial organizations, which ensures the reliability and continuity of the data.
Based on forecast series provided by models and experts, we use a variety of methods to carry out combination forecasts and explore whether forecast combination helps improve forecast accuracy. Specifically, the combination methods include simple averaging, weighting by forecasting errors, and the Bayesian model averaging method based on the Bayesian information criterion.
The predictive information set includes fixed asset investment, total retail sales of consumer goods, total export value, total import value, industrial added value, M2 supply, Shanghai Composite Index volatility, national interbank market interest rate, financial institution RMB loan balances, newly started area of commercial housing, generated electrical energy, consumer expectation index, and national housing prosperity index. We use a multi-dimensional and high-frequency macroeconomic information set to make predicts.
In the out-of-sample comparison, expert forecasts generally outperform model forecasts. The empirical results show that the expert forecasts contain almost all the information predicted by the models, indicating that the experts have considered the predictive content of the models when making forecasts. Furthermore, we find that the accuracy of expert predictions is significantly higher than model predictions during periods of economic instability (2008-2010), as experts can adjust expectations timely by grasping the actual economic environment and the direction of economic policies, and thus obtain more accurate forecasts. In addition, combined forecasting improves forecast accuracy. The robustness tests show that the improvement of forecast accuracy by combination forecasting does not depend on a specific benchmark, and changes in the length of the estimation window do not affect the main findings.
This paper contributes to the existing literature mainly in two ways. First, previous studies that use forecast combination methods to predict China's macroeconomic variables focus on a specific combination forecasting model and discuss its predictive performance. Few studies have considered survey forecast information in the combination forecasting. Compared with model forecasts, expert forecasts are more sensitive to macroeconomic conditions and policy releases, and therefore can continuously update predictive information during forecasting, which improves forecast accuracy. This paper combines expert forecasts and model forecasts by using combination forecasting methods, and examines whether expert predictive information and model forecasting results can help to improve forecasting accuracy simultaneously. Second, this paper compares the forecast performance of expert forecasts and econometric models in different economic periods. We find that expert forecasts significantly outperform model forecasts during periods of economic volatility, and explains the reasons for the difference across economic states.

A bulk of empirical studies have confirmed the spillover effects of U.S. monetary policy on China and other emerging market countries. The U.S. Federal Reserve resumed its quantitative easing policy in 2020. This resulted in the federal funding rate falling to zero, a dramatic expansion of the Federal Reserve's balance sheet, and a global flood of liquidity. Currently, the U.S. economy is gradually recovering, and inflation is rising.It is therefore expected that the Federal Reserve will soon tighten monetary policy and increase the federal funding rate. This implies that emerging market countries, including China, may once again experience a shortage of liquidity and interest rate hikes, in contrast to the current extremely fluid monetary policy. This raises the following three key questions. What are the spillover effects of U.S. monetary policy on China's economy？ What is the mechanism of such spillover effects？ What policies could stabilize the fluctuations caused by these spillover effects？ This paper aims to answer these questions with reference to the Federal Reserve's interest rate hike in 2016.
Based on Davis and Presno(2017),we contruct a small open economy dynamic stochastic general equilibrium model(DSGE)with financial friction and a real estate market.We thereby propose the causative mechanism as follows:The increase in U.S. interest rates generates externalities in the flow of capital, which accelerates the decline of domestic asset prices. This triggers the first feedback channel, which is driven by financial friction, leading to the synergistic decline of domestic investment and asset prices. Thus, the expected return on domestic assets is reduced, which triggers a second feedback channel and further increases capital outflows.
In addition,we use welfare analysis to determine the optimal level of capital account control and its effect on the independence of monetary policy. This reveals the optimal level of capital account control should be moderate, as such control has two opposing effects: capital account control can effectively alleviate the influence of foreign interest-rate shocks on economic fluctuations while it can also decrease the efficient allocation of national wealth. The optimal level of capital account control must therefore balance macro-prudence and efficiency. What's more,we find that appropriate policies for capital account control help to enhance the independence of monetary policy.
In contrast to previous studies, we simultaneously replicate and explicate, within a unified framework, the characteristics of China's macroeconomy subsequent to the U.S. Federal Reserve's interest rate hike in 2016. We also propose a mechanism for the interaction between the feedback channels of capital flow externalities and financial accelerators, which links the spillover effects of U.S. monetary policy with asset price fluctuations. This confirms that China's real estate market is a key channel via which U.S. monetary shocks affect China's economy.
Based on the above findings, we make the following policy recommendations. First, capital account control should be gradually transformed to capital account management. This requires the gradual liberalization of long-term capital account restrictions and the establishment of a regular mechanism for the management of abnormal capital flows. Second, more market-oriented dynamic measures for capital account management should be explored, such as risk reserves, Tobin taxes, and macro-prudential taxes. Third, while the opening of the capital account is gradually and steadily promoted, policies should be developed to increase reform depth and risk prevention. Increasing reform depth requires the marketization of the RMB exchange rate formation mechanism and the opening of the financial market, whereas increasing risk prevention requires the gradual implementation of policy experiments in lower risk fields.

Competitive neutrality involves maintaining a level playing field for competition between public (SOE) and private (non-SOE) enterprises, such that they follow the same rules when competing for business. However, in China commercial banks are the principal players in the credit market, and they commonly practice credit discrimination when they implement financial policies, which is a deviation from competitive neutrality. As such, prior research clearly recognizes that in comparison to SOEs, non-SOEs are at a substantial disadvantage when accessing the credit market.
In response to COVID-19 shock, China introduced a series of financial policies to provide increased monetary and credit support to real sectors, especially to non-SOEs. Thus, we explore whether and how such financial policies affect competitive neutrality following the spread of the COVID-19 pandemic, which represents a unique exogenous experimental scenario.
We use a sample of medium-term notes and commercial papers issued around the time of the outbreak of the COVID-19 pandemic to conduct difference-in-differences tests of the realization of competitive neutrality via financial policy. We find that compared with SOEs, non-SOEs experience a significantly larger reduction in the costs of debt financing during the pandemic period, which suggests that government intervention leads to improved competitive neutrality. Our analyses also show that the reduction in debt-financing costs for non-SOEs is proportional to the amount of trade credit they provide to their partners along the supply chain. Thus, the supply of trade credit by key non-SOEs to other non-SOEs along the supply chain reduces the COVID-19 pandemic-generated financial constraints on these other non-SOEs, thereby serving as an important mechanism to promote the realization of financial policy that ensures competitive neutrality. Furthermore, we find that the supportive financial policies implemented during the pandemic period reduce non-SOEs' level of financialization and improve their efficiency of fund utilization.
Our study makes several contributions. First, it explores an important approach to achieving competitive neutrality via financial policy. Our findings indicate that the credit discrimination against non-SOEs that previous studies document results not from the financial policies themselves, but from commercial banks' partial implementation of these financial policies. These findings highlight better ways to realize competitive neutrality via financial policy.
Second, our study contributes to research on credit discrimination and ownership discrimination. Our findings suggest that the financial policies promulgated by the central bank and other institutes effectively improve the financing environment for non-SOEs during the pandemic period, and the resultant financial support to non-SOEs does not result in resource misallocation or the inefficient use of raised funds. In fact, the improved financing environment for non-SOEs significantly alleviates the credit and ownership discrimination that they usually experience in the debt market.
Third, our study enriches understanding of the complementary relationship between commercial credit and bank debt. We find that a non-SOE’s financial support of its non-SOE trade partners along the supply chain serves as a positive signal, which increases the probability that these trade partners will obtain loans from commercial banks on favorable terms in the event of extreme shocks.
Fourth, our study provides insights into the financial risks embedded within the financial system, which should be monitored by regulators. For example, although the supply of commercial credit may enable non-SOE trading partners along the entire supply chain to obtain financial support and assist financial institutions in implementing policies to ensure competitive neutrality and maintaining controllable levels of credit risks, there is also a risk that this supply may generate contagious financial distress. That is, if non-SOEs in the supply chain default on their loans or declare bankruptcy, this may have a spillover effect on the entire supply chain, leading in extreme cases to financial crisis.

Credit debt is a vital part of the financial market, and an increase in credit defaults has a negative effect on the prevention of systemic financial risks. Thus, the advance identification of default risks has numerous positive effects: it protects the interests of investors, enhances the attraction of credit debt, strengthens the investment and financing functions of the bond market, reduces information asymmetry in the credit bond market, inhibits excessive financing of high-risk enterprises, and reduces leverage ratios and systemic financial risk (via the resource allocation functions of pricing mechanisms).
The traditional tool used to identify credit bond risk is the credit rating, and ratings agencies in China typically use an “issuer-paid” approach for their assessments. However, this approach involves an inherent conflict of interest, as ratings agencies often increase revenue and market share by deliberately upgrading issuers' credit ratings, which makes it difficult to identify the actual default risk of such issuers' bonds. In these circumstances, a key question is, can a third-party valuation of such bonds accurately reveal their expected default risk？ The answer to this question is of great practical significance for optimizing the construction of the bond market information environment and preventing systemic risk.
At present, the mainstream valuation of China's bond market is the ChinaBond valuation, which is issued by the ChinaBond Pricing Center Co., Ltd., after the end of each trading day. A ChinaBond valuation has the following advantages. First, in contrast to a traditional credit rating, a ChinaBond valuation adopts the “investor-paid” approach to assessment, which is more independent than the “issuer-paid” approach. Second, the ChinaBond Pricing Center Co., Ltd., is directly affiliated with the China Central Depository & Clearing Co., Ltd., which discloses information about bond issuers and acts as the central custodian and clearing house for bonds. Thus, the China Central Depository & Clearing Co., Ltd. provides objective conditions for the ChinaBond Pricing Center Co., Ltd. to use to obtain relevant information. Third, in contrast to the Kealhofer, McQuown, and Vasicek model, ChinaBond valuations integrate the market information of bonds with the financial information of bond issuers, and it is released daily to ensure better real-time performance. Fourth, ChinaBond valuations are widely used by regulators for transaction pricing, risk assessment, and fair value measurement. In addition, studies find that the price or yield jumps of assets, such as stocks and options, reflect relevant information on bond issuers and the expected default risk of their bonds, and affect the credit spread. Thus, short-term changes or jumps in a ChinaBond valuation could enable investors to judge the credit risk of bonds.
Accordingly, this paper determines the utility of a ChinaBond valuation for the identification of credit risk by exploring its effect on bond credit spread and the mechanism of this effect in terms of jumps in valuation. Specifically, based on the data of ChinaBond valuations provided by the ChinaBond Pricing Center Co., Ltd. from 2011 to 2018, this paper studies how a jump in a ChinaBond valuation affects bond credit spread. The results show that a jump in such a valuation significantly affects the bond credit spread: an upward jump decreases the credit spread, and a downward jump increases the credit spread. In addition, a downward jump has a greater effect than an upward jump, and a heterogeneity analysis shows that a jump in the valuation of credit spreads has a greater effect on institutional investors and on bonds with severe information asymmetry, poor liquidity, and high default risk. Further research shows that a valuation jump contains private information, in addition to public information, and can be used by stock analysts to improve their forecasting performance.
The key contributions of this paper are as follows. First, current research on the identification of bond credit risk focuses on credit ratings, and few studies discuss this issue from the perspective of third-party valuation. Thus, this paper's analysis of the role of a ChinaBond valuation in credit risk identification provides a new perspective for related research. Second, this paper finds that a ChinaBond valuation not only gives credit risk information on bonds but also provides investors with private information that complements existing public information. This is invaluable for China's bond market, which lacks effective tools for the identification of credit risk. Third, the conclusions of this paper have profound policy implications, as they reveal that third-party valuations can provide more credit risk information than credit ratings. Thus, third-party valuations can serve as a theoretical reference for various contracting parties and government regulatory authorities for guarding against the risk of bond default or for managing a default event, or as a market-based means to protect the interests of creditors.

Targeted poverty alleviation(hereafter: TPA) was proposed by Chinese central government in 2013. TPA requires firms to provide specific and effective assistance to poverty-stricken people throughout China. This assistance should seek to solve the problems that cause people to be trapped in poverty. Accordingly, a number of socially responsible firms have initiated TPA programs.
We summarize that there are three motivations for firms to perform corporate social responsibility (CSR) such as TPA. The first is altruistic motivation, which involves firms giving assistance to others in society without receiving a return. The second is managerial agency motivation, which involves managers using firms' resources to enhance their own social image. The third is strategic motivation, which involves firms performing CSR activities to acquire strategic resources, such as social reputation and political connections. Although there are many studies on CSR,most studies only consider philanthropic donations and do not consider non-cash assistance (e.g., technical and educational assistance). Moreover, previous studies focus on whether and how much firms donate but do not examine whether donations achieve their desired effects. These studies conclude that the motivation of CSR is not altruistic and may be another form of managerial agency cost. We believe that this conclusion may misinterpret firms' motivation to perform CSR.
Thus, we explore firms' motivation to perform CSR by examining whether their motivations to engage in TPA and the effects of their doing so are different from those related to philanthropic donations. Our sample includes all of the non-financial A-share firms listed on the Shanghai Stock Exchange and Shenzhen Stock Exchange. We manually collect firms' implementations of TPA from annual reports and CSR reports. We find that engaging in TPA reduces firms' financial constraints and thus increases firms' performance and shareholder wealth. Furthermore, we find that TPA spurs local economic growth and enhances residents' income within targeted regions. Furthermore, TPA does not cause significant damage to the regional environment. We also find that firms do not participate in TPA to conceal misconduct or to divert investors' attention from stagnant stock prices, which allows us to exclude managerial agency as a motivation. Overall, our findings suggest that firms' participation in TPA is driven by altruistic and strategic motivations and ultimately creates a win-win situation for firms, society, and the environment.
Our findings provide important information for policymakers who devise methods to reduce poverty. Specifically, our findings suggest that the governments should encourage firms to deeply embed themselves in poor regions of the world, as by doing so, firms can use technology and talent to increase the efficiency of poverty alleviation. In addition, subsequent to the implementation of rural revitalization strategies in China, firms should establish long-term mechanisms to systematically achieve rural revitalization. For example, by allocating more advanced technology and talent to rural areas, firms could integrate themselves with local economies and thus obtain returns from resource complementarity.
Our study makes several contributions to the literature. First, we clarify what motivates firms to perform CSR in terms of why they engage in TPA. Studies conclude that firms' motivations to perform CSR are not altruistic and may be used as a tool to achieve managerial goals. However, we evaluate the effects of CSR and find that firms' engagement in TPA is motivated by altruism, suggesting that firms genuinely wish to improve social welfare, rather than to simply pursue managerial self-interest. Our study thus provides a new theoretical perspective that gives a better understanding of what motivates firms to engage in CSR.
Second, our study clarifies whether engaging in CSR produces unilateral benefits or creates a win-win situation. Many papers find that CSR produces benefits for only one party. For example, Chen et al. (2018) find that engaging in CSR reduces a firm's profitability and shareholder wealth. Lu et al. (2020) find that these reductions in profitability and shareholder wealth occur in state-owned enterprises (SOEs) and in non-SOEs; thus, CSR improves social welfare at the expense of shareholder wealth. In contrast, we find that engaging in TPA increases shareholder wealth and promotes local economic growth without damaging the local environment; thus, engaging in TPA can create a win-win situation. This is a new perspective that broadens understanding of the effect of CSR on firms' profitabilities and social welfare.

Since the introduction of the margin trading system in the Chinese A-share market in 2010, the trading volumes and holding balances of margin investors have increased significantly. Today, margin investors hold approximately 1 trillion yuan of A-share stocks, and these investors are thus a key part of the market. There is therefore a need for a better understanding of the trading behavior of margin investors and its effect on the pricing mechanisms of the A-share market. To this end, we exploit the unique data availability of the Chinese A-share market to conduct in-depth analyses of the trading of margin investors to determine how their trading affects market returns and liquidity.
We refer to the predictions of collateral constraint models and hypothesize that margin investors are trend-followers; thus, there should be asymmetry in the relationship between stock price changes and leveraged investors' trading behavior. We observe a significant trend-following pattern in the behavior of margin investors in Chinese stock markets: these investors buy after a stock price increases and sell after a stock price decreases. We find that a stock price decrease has a greater effect on margin investors' trading activity than a similar stock price increase. We further show that this asymmetry is mainly driven by market-level returns.
Specifically, we conduct stock-level time-series regressions in which the weekly net buying activity based on margins is regressed on the lagged weekly stock returns. We find that a significantly positive relationship exists between leveraged net buying activity and past stock returns: if the stock price increases in week t-1, there is a significant increase in the net buying activity by leveraged investors in week t; analogously, if the stock price decreases in week t-1, there is a significant increase in the net selling activity by leveraged investors in week t. We quantify the magnitude of this effect based on the average size of our sample firm (approximately 25 billion RMB) and thus calculate that a 10% stock price change in a given week will lead to a 0.25% (or 44 million RMB) change in the total market cap trading by leveraged investors in the following week.
Next, we test whether there is any difference between the effects of stock price increases and decreases on leveraged investors' trading behavior. Brunnermeier and Pedersen (2009) suggest that a loss spiral may occur in some price-decrease circumstances, where an initial price decrease caused by an exogenous shock can lead to leveraged speculators experiencing losses on their existing positions, causing them to de-leverage by selling, which causes further price decreases, and thus continued selling. In addition, when a market increases in value and leveraged investors can borrow more, they are free to choose whether to make additional stock purchases, but when a market decreases in value and leveraged investors are affected by funding or collateral constraints, they are compelled to sell their portfolio holdings, especially if they receive margin calls. Therefore, we hypothesize that the effect of stock price decreases on leveraged investors' trading behavior is stronger than the effect of stock price increases on their trading behavior.
We find that there is indeed significant asymmetry in the relationship between stock price changes and leveraged investors' trading behavior: specifically, the effect of a stock price decrease on leveraged trading activity is approximately twice the effect of a stock price increase of the same magnitude on leveraged trading activity. This means that a 10% price increase of an average stock in a given week will lead to net buying of approximately 0.13% of the market cap by leveraged investors in the following week, whereas a price decrease of 10% will lead to net selling of 0.24% of the market cap by leveraged investors in the following week. Notably, these differences are statistically significant, and thus provide direct support for the predictions of the Brunnermeier and Pedersen (2009) collateral constraint model. Furthermore, we find that the asymmetric relationship between stock price changes and leveraged trading behavior strengthens in good economic times, which is consistent with the theoretical predictions of Acharya and Viswanathan (2011).
We also explore the return predictability of leveraged trading activity. We observe that a significantly negative relationship exists between net leveraged buying activity and subsequent stock returns. In addition, we find that the negative relationship between leveraged investors' trading activity and their subsequent weekly stock returns is primarily attributable to the selling behavior of margin investors.
Overall, our paper provides strong empirical support for collateral constraint models. We also provide policy recommendations on how the resilience of Chinese stock markets could be improved.

The pay gap between corporate executives and ordinary employees is related to both the company's performance and the fairness and stability of social distribution.Government departments have promulgated a series of policies and regulations to limit the pay gap. However, these salary-limiting policies have mainly been imposed by external regulatory forces, and their implementation has not been uniform; in addition, these policies have had a limited effect on non-state-owned enterprises. In this context, the internal governance perspective suggests that it is necessary to study the issue of executive salaries from the ground up, which is also instructive for understanding the pay gap in different companies.
The board of directors is the core of a company's internal governance. Exploring the factors influencing the board's supervisory function will clarify the causes and consequences of the pay gap. Unlike the literature focusing on individual characteristics, our study is based on faultline theory. With the extension of the company's operating time, the board of directors may form different small groups. Small groups have different profit-seeking motives, and differ in management concepts, methods, and awareness, which makes it difficult for the board of directors to perform its supervisory function effectively. The phenomenon of multiple small groups within the board of directors is called “board faultlines”. Such faultlines are common and have a serious impact on its functioning. Accordingly, we explore whether the existence of small groups within the board of directors affects its supervisory function and the firm pay gap.
Based on data from a sample of Chinese A-share listed companies from 2005 to 2019, we examine how board faultlines affect the firm pay gap. Our findings suggest that (1) board faultlines significantly promote the pay gap; (2) board faultlines based on deep-level attributes have stronger and more persistent effects on the pay gap; (3) a high degree of industry competition alleviates this positive relationship;(4) the impact of board faultlines on the pay gap leads to lower firm performance.
Our study makes three contributions to the literature. First, we enrich research on pay gap governance from the perspective of board faultlines. We find that the harm to the board's supervisory function caused by board faultlines is a source of executive power. Therefore, attempts to address the pay gap should examine the formation of board faultlines. Our study thus provides a new direction for pay gap governance research and practice.
Second, we contribute to research on the measurement and economic consequences of board faultlines. We consider eight director characteristics and optimize the measure, overcoming the limitation of the number of subgroups and making the measure more accurate. In terms of economic consequences, studies typically focus on corporate performance, value, and cross-border mergers and acquisitions.Our study discusses the impact of board faultlines on the board's supervision and the firm pay gap, which constitutes a useful supplement to the literature.
Third, our findings have practical significance for improving the company's salary incentive mechanism and board supervision. We find that the pay gap does not have an incentive effect, and even has a negative impact on corporate performance. Therefore, the company should pay attention to the reasonable combination of director characteristics when choosing directors. It is important to prevent the formation of faultlines while achieving diversification of the board of directors, to emphasize the board's overall goal, and to alleviate the harm of identity with a subgroup. These measures will improve board supervision and compensation incentives.

China has made remarkable progress in high-speed railway construction over the past decade, and it now ranks first in the world in terms of total mileage. Compared with other modes of transportation, high-speed railway has many advantages, being faster, safer, and more environmentally friendly. However, little attention is paid to its effect on the capital market. As a core concept in corporate finance, the cost of equity capital has always been of interest to researchers. At the micro level, this cost is an important criterion for the selection and performance evaluation of investment and financing projects and is vital for financial and business decisions. At the macro level, it plays an important role in efficient resource allocation and capital flow, and is an important indicator of the development of the capital market and the construction of relevant institutions (Mao et al., 2012). Therefore, understanding the spatiotemporal constraint effect of high-speed railway on the cost of equity capital will provide useful insights into the operation of the capital market, corporate investment, financing decisions, and performance evaluation.
Taking China's A-share listed companies from 2007 to 2018 as a sample, this paper empirically investigates whether the opening of a high-speed rail has an impact on the equity capital cost of local listed companies. If so, is the impact different according to the companies' characteristics？ What are the specific paths by which the opening of a high-speed rail affects the cost of equity capital？ The results show that the cost of equity capital decreases significantly after the high-speed rail opens near the listed companies due to the reduction in internal and external information asymmetry. This phenomenon is affected by a series of company characteristics.The more distant the company is from the majority of investors, and the higher the company's business complexity is, the more the cost of equity capital is affected by the opening of the high-speed rail. Subsequently, we find that the improved company stock liquidity and information disclosure quality after the opening of a high-speed rail both affect the cost of equity capital. A series of robustness checks, including placebo tests, a two-stage regression, and propensity score matching, confirm the results of this paper.
The contributions of this paper are as follows. First, it systematically investigates the impact of high-speed railway on the cost of equity capital, which improves our understanding of the spillover effect of high-speed rail operations and provides micro-enterprise evidence of the economic consequences of high-speed railway in China. Second, this paper investigates the effect of high-speed railway on the cost of equity capital, and then examines the channels of influence, enriching research on companies' cost of equity capital.
Our findings have the following practical implications. (1) Accelerated construction of transportation infrastructure will ensure the high-quality development of the real economy. (2) No matter what new characteristics and new forms of business appear in the operation of the capital market under the new situation, improving listed companies' quality of information disclosure, reducing transaction costs, and optimizing the efficiency of capital market resource allocation should be basic construction projects to cultivate the capital market. (3) Geographical location and distance from megacities cannot be changed, but the continuous search for spatiotemporal compression and changes in the spatial structure, distribution structure, and hierarchical structure enlarges the driving effect of central cities, especially megacities, i.e. Beijing, Shanghai, Guangzhou, and Shenzhen.