As population aging advances, China's traditional capital and labor driven growth pattern is becoming increasingly unsustainable. China's growth transition must be accelerated. The Outline of the 14th Five-Year Plan and Vision 2035 explicitly states that China needs to effectively transform its growth pattern and promote changes in the quality, efficiency and drivers of growth. The main objectives of the growth transition are to improve the contribution of total factor productivity (TFP) to economic growth and to stimulate new drivers of economic growth. Countries that demonstrate higher levels of aging also tend to contribute more TFP to economic growth. However, a critical phenomenon that cannot be ignored is that a high TFP contribution does not lift aging economies out of stagnation, as demonstrated by Japan and some European economies.
This background leads to the focus of this paper, namely whether increasing the TFP contribution rate can effectively counteract the impact of aging on economic growth. This issue is both controversial and innovative, but it also has important practical significance for China and can yield guidance on how to better realize Chinese-style modernization with such a large population. Hence, based on the Penn World Table (version 10.0), this paper adopts the production function method to measure the TFP levels and their contribution to growth in 90 economies from 1961 to 2019. A regression model is constructed to analyze the effect of increasing TFP contribution on economic growth in an aging population, using cross-country panel data.
This paper draws three main conclusions. First, the aging rate is positively correlated with the TFP contribution rate. However, the increased TFP contribution stems mainly from a “passive rise” due to the rapid decline in traditional growth drivers, rather than an enhanced role of TFP in driving the economy. Second, as the aging rate increases, the promoting effect of the increased TFP contribution on economic growth weakens significantly. This finding holds after excluding the effect of the passive rise in the TFP contribution rate. Overreliance on increasing TFP to counteract aging makes economies prone to a situation characterized by high TFP contribution and low growth. Third, the subgroup regression shows that neither the TFP-driven pattern nor the traditional capital and labor driven growth pattern has any significant advantage in coping with population aging. Furthermore, the effect of aging on economic growth is negative and significant. The growth pattern that emphasizes both TFP and traditional growth drivers is more effective in mitigating the negative impacts of aging on economic growth, making such impacts insignificant.
This paper makes three contributions. First, it proposes and systematically demonstrates the passive rise of the TFP contribution rate in an aging context. This finding enhances the understanding of the problem posed by a high TFP contribution rate in an aging economy for all sectors of society. Second, this paper systematically analyzes the effect of increasing the TFP contribution rate to counteract aging. Studies usually focus on the role of TFP alone in aging contexts, neglecting the fact that factors such as TFP, capital, and labor are the main components of a growth system and are closely interconnected. From the perspective of the entire growth system, this paper finds that a growth pattern that emphasizes both traditional and new drivers is more helpful in offsetting the effects of aging than a TFP-driven growth pattern, which is a novel finding. Third, this paper presents a systematic measurement of the level of TFP and its contribution rate in major economies around the world, and it develops a relatively rich cross-country empirical study, which provides new empirical evidence for analyzing the growth transition in the process of aging.
The findings of this paper have valuable policy implications. China's TFP contribution to economic growth is currently low. Thus, in the face of aging, it is necessary to improve the TFP contribution to economic growth, and to transform the previous growth pattern driven by capital and labor. Furthermore, while increasing the TFP contribution rate, the weakening of traditional growth drivers should not be ignored. A TFP-driven growth pattern would be much less growth-enhancing, as it would be difficult for TFP to offset the decline in traditional factors' growth in an aging context. Therefore, China should break through the traditional understanding of existing theories, organically combine the strategy of innovation-driven development with the strategy of expanding domestic demand, and construct a new growth pattern that considers the interplay between both new and traditional growth drivers, so as to better respond to the challenges of aging and meet the growth rate required for the realization of socialist modernization.

The scale of China's shadow banking sector continues to expand in recent years. Non-financial enterprise sectors are engaging in financial asset investment activities.This has led more enterprises to shift human resources and capital from their original production and operation areas to financial asset investment and shadow lending activities. The shadow banking of enterprises decreases the physical investment rate and exacerbates systemic financial risks. Since the 1990s, global central banks have gradually increased their emphasis on central bank communication and used it as a means of macroeconomic policy regulation. The central bank uses verbal communication to announce the direction of its future monetary policy implementation, which helps the public form expectations about changes in the economic state, sufficient credit liquidity, and financial regulatory intensity, thereby influencing the behavior of micro residents and enterprises. Therefore, leveraging the regulatory role of monetary authorities in the investment and financing behavior of micro enterprise entities, exploring methods to resolve financial risks, and curbing the excessive development of the shadow banking system have become important efforts for government decision-making departments and domestic and foreign scholars.
This paper constructs a dynamic stochastic general equilibrium model to simulate the relationship between central bank communication and corporate shadow banking business. Then, based on quarterly data from listed companies from 2007 to 2020, it conducts an empirical analysis of the relationship between central bank communication and the shadow banking of non-financial enterprises. This paper makes three main contributions. First, starting from the perspective of central bank communication, it analyzes the reasons for changes in the corporate shadow banking scale. It also proposes the impact of central bank communication on the shadow banking of non-financial enterprises, which has a strong innovation in research perspective. Second, this paper explores and elaborates on the mechanism through which central bank communication affects the shadow banking of non-financial enterprises, and it theoretically supplements existing research. Third, this paper examines the impact of the consistency of the central bank's words and actions on the shadow banking of non-financial enterprises, thus further supplementing and extending the theoretical research on central bank communication.
The findings indicate that central bank communication can inhibit the shadow banking behavior of non-financial enterprises. The above effects are enhanced in companies whose executives have a financial background, a strong awareness of social responsibility, and low corporate governance efficiency. The mechanism analysis shows that central bank communication suppresses the shadow banking of non-financial enterprises by suppressing the degree of financial mismatch, improving investment stability, and reducing the difference between financial and physical returns. Central bank communication can not only alleviate heterogeneous investor beliefs but also reduce divergence in analyst predictions. The impact of central bank communication meetings on enterprises and capital market participants is mainly reflected in reducing investor belief heterogeneity and analyst prediction divergence. In addition, the consistency of the words and actions of the central bank has a negative impact on the shadow banking of non-financial enterprises, while risk warning communication has a reverse regulatory effect on the relationship between central bank communication and enterprise shadow banking.
Based on the findings of this paper,two policy recommendations can be made. First, the important role of central bank communication in stabilizing expectations and adjusting economic structure must be emphasized, the coordination and cooperation between traditional monetary policy and central bank communication must also be underscored, and the important role of central bank communication in managing public expectations, improving resource allocation efficiency, and stabilizing investor sentiment must be fully leveraged. Second, the transparency of monetary policy must be enhanced, the functional supervision of regulatory authorities must be strengthened, the timely disclosure of relevant information (e.g., on corporate operations and finances) must be reinforced, and the degree of information asymmetry among capital market participants must be alleviated to curb the rampant growth of shadow lending behavior.

Work related to China's current capital market is focused on expanding its high-level institutional opening. Since the 18th National Congress of the Communist Party of China, the dual-track opening of the capital market has accelerated. The “Shanghai-Hong Kong Stock Connect,” “Shenzhen-Hong Kong Stock Connect,” and “Bond Connect” mechanisms have been successively launched and gradually optimized. However, compared with the vibrant practice of the capital market, academic research on the opening of the capital market focuses mainly on the stock market, paying less attention to the policy effects of bond market opening. The opening of the bond market is an important part of China's dual-track capital market opening, playing a significant role in promoting the internationalization of the renminbi, deepening market-oriented interest rate reform, and constructing a new open economic system. Given its considerable market size and risk spillover effects, the bond market is systemically important for the stable development of China's financial market. With the increasing opening of China's bond market to foreign investors, this paper focuses on whether foreign bondholders, as important participants in the bond market, affect the operational efficiency and corporate bond credit risk of the Chinese bond market.
The launch of Bond Connect has created a favorable natural setting in which to study the impact of bond market opening on credit spreads. Based on the quarterly data of corporate bonds and medium-term notes issued by listed companies from 2014 to 2020, this paper takes the implementation of Bond Connect in July 2017 as an exogenous shock. The issuances and transactions of medium-term notes in the interbank bond market affected by the policy are treated as the experimental group, while the issuances and transactions of corporate bonds in the exchange bond market unaffected by the policy are treated as the control group. The impact of bond market opening on credit spreads is examined using a difference-in-differences model. The results show that Bond Connect has significantly reduced credit spreads for corporate bonds. The mechanism analysis indicates that Bond Connect reduces credit spreads through liquidity effects, information disclosure effects, and external supervision effects. This paper conducts a heterogeneity analysis from the perspective of bond characteristics and finds that the negative impact of Bond Connect on credit spreads is more significant in the samples with smaller bond issuance sizes, no special terms, and lower bond ratings. Further analysis reveals that Bond Connect implementation not only reduces credit spreads in the secondary market but also affects the primary market by reducing primary market spreads for corporate bonds, improving issuance efficiency, and significantly increasing the number and scale of bond issuances by companies.
This paper makes several contributions to the literature. First, as an important measure of the capital market's institutional opening, Bond Connect has been running for more than 6 years since July 2017. However, the literature focusing on its impact on credit risk in the bond market remains limited. This paper systematically analyzes the impact of Bond Connect on the credit spreads of corporate bonds and its operating mechanisms, enriching the relevant literature on bond market opening and providing strong evidence of the effectiveness of Bond Connect. Second, research on credit spreads mostly focuses on macro environments, corporate governance, and bond terms. In particular, studies on the impact of capital market opening on credit spreads mainly focus on the stock market. However, the bond market and the stock market differ considerably in terms of investor structure, investment product attributes, and investment risks. The conclusions of research on overseas stock investors usually cannot be directly applied to overseas bond investors. This paper uses the Bond Connect opening policy to directly examine the impact of foreign bondholders on mainland bond market risks, to some extent enriching the research on bond market risks. Third, this paper's findings show that bond market opening can reduce the credit spreads and increase the financing scale of corporate bonds, reflecting the role of bond market opening in optimizing global resource allocation, preventing and resolving financial market risks, and promoting the high-quality development of China's capital market. The conclusions of this paper highlight the importance of bond market opening for the healthy development of micro-enterprises and even the capital market in China, providing some enlightening implications for “the new development paradigm with domestic circulation being the mainstay and the two circulations reinforcing each other.”
This paper yields some important policy implications. First, it is necessary to firmly promote high-level financial opening and construct the new development paradigm. This paper links capital market opening with bond market credit risk, thus providing new microeconomic empirical evidence for the study of financial market opening and stability. It is highly important for preventing and resolving financial risks and promoting the healthy and stable development of the financial market. Second, bond market opening can improve the accuracy of pricing for bond issuers, allowing them to reduce financing costs and attract more funds into the bond market, thereby increasing the demand and activity of the securities market. This benefits both bond issuers and investors and enables the financial sector to better serve the real economy. The findings of this paper encourage further promotion of the transformation of China's bond market from factor flow-oriented opening to rule-based institutional opening to advance the reform, opening, and high-quality development of the bond market.

Equity pledge financing has become a prevalent method used by the shareholders of listed companies in China to pursue debt financing. In recent years, sharp declines in stock prices due to an equity pledge, resulting in the risk of debt default and significant losses for pledgees, have become increasingly common occurrences. Studies demonstrate the existence of moral hazard and adverse selection issues in the credit market. The occurrence of equity pledge financing hinges on the willingness of shareholders to pledge their equity for financing and the readiness of financial institutions to accept such equity pledges and provide financing. However, due to asymmetric information between pledgers and pledgees, financial institutions may be conservative when determining pledge rates, making it challenging to accurately assess the risk of a company's stock price collapse. This may lead financial institutions to set low pledge rates for stocks of “good companies,” causing pledgers to abandon transactions, and high pledge rates for stocks of “bad companies,” making pledgers more willing to accept transactions. In essence, a “lemon phenomenon” may exist in the equity pledge financing market due to information asymmetry. This phenomenon not only adversely affects the companies directly by increasing the risk of stock price collapse but also has spillover effects through the “association” of equity pledges. Regulating and guiding the healthy development of capital in accordance with the law, as well as preventing and resolving systemic financial risks, are important measures to promote high-quality economic development in China. Clarifying the issues arising from the lemon phenomenon in the credit market not only contributes to the literature on credit market information asymmetry and the factors influencing equity pledges, but it also provides valuable insights into mitigating the propagation of stock price collapse risk from the capital market to the credit market and the potential systemic financial risks.
In this context, this paper focuses on Chinese listed companies from 1999 to 2019, using a large-sample regression method to empirically test the impact of stock price crash risk on shareholders' share pledge behavior. It finds that corporate stock price crash risk increases shareholders' share pledge transactions, indicating the presence of the information asymmetry issue whereby “bad money drives out good money” in pledged equity financing. The robustness tests confirm the reliability of the findings. Further research shows that the positive relationship between stock price crash risk and equity pledges is more pronounced in state-owned enterprises and companies with a larger scale, lower equity balance, and weaker growth, and that elevated stock price crash risk exacerbates the effect of equity pledges on increasing the risk of stock closure.
This paper yields three key research innovations and contributions. First, it provides evidence of and enriches the literature on information asymmetry issues in the credit market and the factors influencing equity pledge transactions, both domestically and internationally. The literature on the factors affecting equity pledges is limited, lacking a focus on information asymmetry in the credit market. Second, this paper extends the examination of the economic consequences of stock price crash risk from the capital market to the credit market. In doing so, it expands the research on the economic consequences of a company's stock price crash risk and, based on the quasi-natural experiment of the Shanghai Stock Exchange's “Audit Committee Disclosure,” effectively alleviates endogeneity issues, thus strengthening the causal effect of a company's stock price crash risk on shareholders' equity pledges. The literature examining whether and how a company's stock price crash risk affects its financing behavior is scarce, and this paper discovers that the probability and extent of shareholders' equity pledge financing are positively affected by a company's stock price crash risk. This effect is more significant in state-owned companies, larger companies, companies with lower equity balance degrees, and companies with poor growth prospects. As stock price crash risk escalates, it exacerbates the negative impact of increased equity pledges on stock liquidation risk. Third, both the revealed information asymmetry issues and the lemon phenomenon in the equity pledge financing market have important policy implications and decision-making references. This paper not only provides empirical insights into optimizing financial equity pledge rates but also offers a decision-making basis on which regulatory authorities can formulate and improve the disclosure system for listed firms and accounting supervision policies in capital markets. Ultimately, it contributes to averting the transmission of stock price crash risk from the capital market to the credit market and preempting potential systemic financial risks.

Achieving China's international commitment to “carbon peak” and “carbon neutrality” at a lower social emission reduction cost is the goal of the carbon emissions allowance (CEA) trading market and a central issue in the field of green finance. In 2023, the Central Financial Work Conference emphasized that one of the key channels for providing high-quality financial services is to dedicate more resources to promoting “green development.” Although the CEA trading market has significantly reduced the carbon emissions of the power industry, investors' weak incentive to participate in trading CEA has hindered the discovery of CEA prices. Little theoretical literature explores how to manage CEA to improve the function of CEA price discovery. However, the answer to this question should form the basis from which the CEA trading market can effectively promote green development.
CEA trading originates from the Coase property rights theory, which states that after property rights are clarified, pollution rights trading is the most effective way to solve environmental pollution problems through the market. In terms of the initial allocation of CEA quotas, the Ministry of Ecology and Environment in China has introduced the “2019-2020 National Carbon Emission Trading Quota Setting and Allocation Implementation Plan (Power Industry).” However, this allocation method does not consider uncertainties. Uncertainties affect the demand for CEA quotas, leading to excessively low or high carbon prices, which not only damages corporate value (“transformation risk”) but also squeezes out low-carbon transformation investment. In addition, the lack of risk hedging tools related to CEA assets (“incomplete market”) makes it more difficult to manage CEA price risk. If the CEA trading platform shared the transformation risk by managing CEA quotas, investors would be more willing to participate in CEA trading, and the costs of low-carbon transformation for enterprises would decrease. From a theoretical perspective, three questions remain unanswered. First, how should the trading platform manage CEA in the incomplete market？ Second, what are the mechanisms through which CEA management affects carbon prices and corporate decision-making？ Third, what measures can help enterprises achieve green and low-carbon transformation and control carbon price risk？
To address the above questions, we build a risk management model that integrates firms with heterogeneous emissions intensity, CEA trading, and market incompleteness based on dynamic inventory management theory. First, we use dynamic programming techniques to elucidate the logic behind optimal decision-making for firms and the trading platform. Second, through numerical analysis, we shed light on the risk-sharing of CEA management, carbon price formation mechanisms, and carbon reduction incentive provision. Finally, we explore the impact of advancements in emissions reduction technologies and the establishment of carbon price floors. This analysis helps provide policy recommendations.
We identify three main functions of the CEA management mechanism. First, it provides a channel for high-carbon-emissions enterprises to invest in CEA quotas and hedge carbon price risks, which reduces the cost of low-carbon transformation. Second, it allows low-carbon enterprises to sell surplus CEA quotas and thus manage CEA price risks more effectively. Third, the steady-state level of CEA quotas constrains the total carbon emissions of the power industry, and the dynamic evolution of carbon emissions provides a reference for the dynamic path toward achieving carbon peak.
We make three key contributions to the literature. First, we combine the Coase property rights theory and dynamic inventory management theory, integrate the opinion equating the essence of inventory management with risk management into the design of the carbon quota management mechanism, and point out how the government (i.e., CEA trading platform) and enterprises can reasonably share risk in an incomplete market through CEA management. Second, three measures can be taken to simultaneously achieve low-carbon production and controllable market risks. The first measure is to increase counter-cyclical fiscal support for the trading platform, which can substantially enhance the risk-taking ability of the platform. Consequently, this measure can not only increase the value of carbon allowance investment but also accelerate the green transformation of enterprises. The second measure involves allocating more financial resources to carbon trading. Financial institutions can provide enterprises with professional services such as carbon trading consulting and custody, which can enhance enterprises' ability to suffer risk. Furthermore, developing CEA forwards and swaps and other derivatives helps enterprises hedge transformation risks. The third measure is government introduction of tax reduction policies to incentivize emissions reduction technology innovation and the implementation of differentiated policies for high-carbon enterprises and low-carbon enterprises, which would help to fully realize the synergistic effect of different enterprises in reducing emissions. Finally, the interactive effect between open market operations and price control plays a crucial role when implementing the CEA adjustment policy. For example, a price limitation policy could encourage low carbon production and reduce the market risk in the short run, but it would break the risk-sharing mechanism, resulting in platform bankruptcy risk.

The Resident Basic Medical Insurance (RBMI) plan, as the largest social medical insurance plan in the world, delivers protective health coverage to all non-working groups in China, with the goal of ensuring the affordability of medical services. As a basic medical insurance program designed to cover the entire population, RBMI initially charged residents extremely low premiums and was maintained by high financial subsidies. Nonetheless, in recent years, rising medical expenses and mounting financial strain have resulted in an increase in RBMI premiums, and its average growth rate has exceeded China's high-speed per capita GDP growth rate. Due to the voluntary enrollment principle and the quota contribution model, which means that residents in the same region pay the same premium regardless of their family's income and wealth, rising premiums may lead to more and more people not being covered by the program. Recent decreases in RBMI enrolment underscore this worsening predicament. Therefore, the accurate estimation of RBMI demand price elasticity has become an increasingly important prerequisite for the reasonable formulation of individual premium standards and the improvement of the medical insurance financing model.
Analyzing data from the China Health and Retirement Longitudinal Survey, a two-way fixed-effect model is used to estimate the price elasticity of RBMI demand. The results show that at the national level in 2022, a 10% upsurge in RBMI's individual premium standard significantly reduces enrolment probability by 0.15%, potentially leaving millions uninsured. The results of the heterogeneity analysis of groups with different characteristics show that compared with high-income groups, the demand price elasticity of middle-income groups is significantly higher. Furthermore, due to the original lower participation rate of low-income groups, the increase in premium standards is expected to crowd out the basic medical insurance needs of people with lower socioeconomic status. We note an adverse selection issue where fewer healthy individuals exhibit higher demand price elasticity, opting to stay in the program and thereby potentially escalating per capita healthcare costs and thwarting RBMI's goal of balancing income and expenditure via premium increases. Compared with residents in urban areas, residents in rural areas, which lack formal jobs, are more likely to be the target population of RBMI. As a result, the insurance needs of rural residents' families are higher. This paper demonstrates that the enrollment decisions of rural residents make them more susceptible to the impact of increasing premium standards.
Our subsequent analyses provide empirical evidence that linking payment standards to local residents' per capita disposable income can ameliorate the decline in RBMI coverage. Through a comparative analysis of different types of financing models, this paper outlines the policy implications for the development of RBMI financing models. First, in the process of premium adjustment, the price elasticity of the demand of the insured group should be considered. Furthermore, to increase coverage and balance out one's contribution burden, differentiated premium standards should be set according to the difference in the demand price elasticity. Second, the subsidy scope of low-income people who participate in RBMI should be expanded under the existing quota contribution model. In addition, the low-income subsidy model, which has a lower requirement for income accounting, should be improved. Third, the financing model should be gradually reformed from a quota contribution model to a rate model (i.e., based on family income and property), given that a more powerful and effective household income and property accounting system has been established.
This paper makes three contributions to the literature. First, it provides evidence that premium standards play a fundamental role in enabling the national social medical insurance system to perform the required safeguarding function in developing countries. Second, this paper shows that welfare inequality induced by medical insurance can occur at the early enrollment stage. Finally, it offers an initial rationale for discrepancies in the demand price elasticity of medical insurance across different populations, thereby laying the groundwork for more comprehensive research in the future.

Pension expectations are the critical path connecting the public pension system to individual decision-making, and they directly affect individual welfare through economic variables such as savings and labor supply. Incorrect expectations of future pensions can lead to individual decision-making that deviates from the optimal path, fails to maximize lifetime welfare, and weakens the welfare effects of public pension system reform. Therefore, it is necessary to analyze the main factors affecting the accuracy of pension expectations to provide a decision-making reference for further improving the public pension system. Using data from the China Health and Retirement Longitudinal Study from 2011 to 2018, we examine the impact of experience with the former Rural Residents' Pension (ORBP) on the accuracy of pension expectations among rural residents via the treatment effect model. We find that such experience significantly reduces the degree of pension expectation bias by 0.24, or 34.29% of the sample mean (0.70). This finding holds across several robustness tests, including using the propensity score matching method, restricting the sample to those without migration history, taking into account the sample attrition problem, and shrinking the tails of pension-related variables. We also find the effect to be strengthened among well-educated individuals, those with Internet access, and those without cognitive impairment. In addition, the above effect mainly works by increasing the level of individual caution. The village-level analysis, which uses the cohort difference-in-differences approach, also supports our main findings.
Two policy implications can be drawn from the above conclusions. First, we should objectively evaluate the achievements of the historical exploration of the ORBP, and we should not reject it completely because of the exploration's failure. The historical exploration of the ORBP that began in the 1990s regrettably failed, but it was valuable nonetheless. It not only helped guide the subsequent construction of the New Rural Residents' Pension but also significantly improved the accuracy of residents' pension expectations through several channels, such as increasing the degree of prudence and consolidating the cognitive foundation of pensions. From this point of view, the government should actively explore the construction of various types of public systems. After all, practice is the only standard for testing the truth. However, we must also understand that the realization of the educational function of the ORBP will come at a cost, which can be avoided through a more sophisticated system design. Second, the government should focus on groups with lower levels of cognition. We find that lower levels of cognition can significantly hinder the ORBP from exerting the pension expectation accuracy enhancement effect. Thus, differentiated arrangements are needed to provide more accurate institutional education and information disclosure for groups with lower cognition levels, such as those with lower education, a lack of access to information, and cognitive barriers, to help them better understand the public pension system reform and make reasonable pension arrangements accordingly.
We make two main contributions. First, in terms of research ideas, we integrate experience with the ORBP into impact factors of pension expectation accuracy. This offers a new perspective from which to interpret pension expectation bias and expands the application scenario of the experience learning effect. Second, we verify that the ORBP significantly improves the pension expectation accuracy of the Residents' Basic Pension participants, demonstrating its positive role in improving the level of residents' pension cognition. This result provides new evidence to support objectively evaluating the impact of the ORBP.
In this paper, we explore the impact of experience with the ORBP on the accuracy of pension expectations among rural residents. Limitations pertaining to the calculation method and the impact mechanisms point toward two ways in which future research can be expanded. First, by obtaining longer-term micro-survey data, future research can use residents' expected and real pensions to calculate their pension expectation bias. Second, by obtaining policy trust variables and pension cognition level variables, future research can further characterize how experience with the ORBP affects the accuracy of rural residents' pension expectations.

Labor income share is a major issue concerning people's livelihood and is also closely related to long-term social stability and sustained economic growth. The report of the 20th Party Congress considers increasing people's income level as an important factor for realizing the common wealth of all people. It explicitly states that doing so is necessary to improve the order of income distribution, regulate wealth accumulation, and increase the share of residents' income in the distribution of national income. Once finance deviates from the essence of serving the economy and overrides the real industry, it will distort the distribution share between capital and labor. Based on China's strict financial regulation system, which guides the flow of social capital from the financial system to the real economy, this paper examines its impact on the share of labor income and the underlying mechanism, shedding light on the role of financial regulation in increasing the share of labor income.
In 2018, the People's Bank of China, together with a number of departments, issued the Guiding Opinions on Regulating the Asset Management Business of Financial Institutions (the “New Regulations on Asset Management”) to regulate the development of the asset management business in the financial market and informal financing, as represented by shadow banking, and to urge the return of capital to the real economy. Under strict financial regulation, enterprises return to the real business and can then cause an increase in the share of labor income. This is because financial investment income, which is independent of the production process, limits labor's right to claim the distribution of financial investment income. In contrast, as labor is an important input in the value creation of real businesses, it has bargaining power to participate in income distribution. Furthermore, due to strict financial regulation, enterprises are increasingly reliant on real channels for profitability. This in turn prompts enterprises to increase high-skilled labor, which is necessary for improvement in both production technology (e.g., technological research and development) and production processes. Thus, given the strict financial regulation, increased demand on high-skilled labor by firms will also increase the share of labor income.
Using a sample of non-financial listed firms in China, we construct treatment and control groups based on the degree of financialization of the firms before regulation. The difference-in-differences results show that compared with the control firms, the share of labor income of the treated firms increases by approximately 3.5% after the implementation of the new regulations. Upgrading labor skills under strict financial regulation is important. The cross-sectional results show that the new regulation has a more pronounced effect on labor income share when firms demonstrate over-financialization, employ executives with financial backgrounds, are located in regions with higher levels of private financial development, and have labor with stronger bargaining power. Finally, we find that strict financial regulation mainly increases the income share of rank-and-file employees, rather than executives, and the income gap between executives and employees decreases.
This paper identifies a key factor in increasing the labor income share from a new research perspective. Previous studies examine the determinants of labor income share from the perspectives of the institutional environment, economic structure, and workers' bargaining power at the micro level. Few studies examine the impact on labor income share from the perspective of financial market development. Focusing on financial regulation, this paper finds that strict financial regulation is an important factor in raising the labor income share. It enriches and extends the research on the economic consequences of financial regulation by examining its impact on labor income distribution. Finally, this paper finds that strict financial regulation increases the income share of rank-and-file employees, rather than executives, and the income gap between executives and employees decreases, which has policy implications for adjusting income distribution and promoting common prosperity.

Difficult and expensive financing in the field of agriculture, rural areas, and farmers is a longstanding issue. It stems from the inability of the traditional credit model to break through the “triangular dilemma” of rural credit services; that is, traditional financial institutions cannot simultaneously achieve their three goals related to risk (controllability), cost (sustainability), and scale (growth) when offering rural credit services. In the context of accelerating the most recent round of scientific and technological revolution and industrial transformation, the broad application of the new generation of information technology (represented by big data, cloud computing, and artificial intelligence) in the financial field is promoting profound changes in financial formats, financial products, and financial development models, as well as constantly improving the quality and efficiency of financial services. Therefore, fintech is regarded as an important and feasible means of alleviating the abovementioned triangular dilemma.
At present, in the face of external challenges brought by “the sinking of large banks' business and cross-border competition of fintech companies” and the internal pressure caused by “narrowing interest margins,” rural financial institutions have taken digital transformation to an unprecedented strategic height. However, this situation differs from that of large banks that establish fintech subsidiaries with great financial strength, solid customer bases, and strong research and development capabilities. Multiple constraints (e.g., the lack of fintech talent, limited financial strength, and complex management systems) make it difficult for rural financial institutions to independently establish fintech subsidiaries or invest large amounts of money into the development and application of fintech, resulting in widespread “digital transformation anxiety.” In this context, a large number of rural financial institutions have signed strategic cooperation agreements with fintech companies, aiming to innovate their business models, optimize their service processes, and improve their risk management through cross-border cooperation, with the goals of promoting their digital transformation and effectively alleviating the difficulty and high costs of financing. Has the cooperation between rural financial institutions and fintech companies achieved the expected results？ Can such cooperation shape their competitive advantage related to inclusive finance, break through the bottleneck of rural financial development, and ultimately solve the triangular dilemma problem？
This paper takes rural financial institutions' signing of strategic cooperation agreements with fintech companies as a quasi-natural experiment. Based on the annual data of 641 rural financial institutions in China, this paper uses a multi-period difference-in-differences (DID) model to investigate the impact of fintech on the credit scale, credit risk, and operating costs of rural financial institutions. It finds that fintech can expand the credit scale of rural financial institutions and reduce their credit risk without increasing their operating costs. This means that fintech can indeed alleviate the triangular dilemma of rural credit services. The mechanism analysis shows that the alleviation of information asymmetry is an important factor in fintech's ability to improve the credit scale and quality of rural financial institutions. Further analysis shows that fintech can expand the retail loan scale of rural financial institutions and improve their operating performance; improving net interest income is important for the improvement of rural financial institutions' operating performance.
This paper makes three contributions. First, in terms of research, it extends the literature on the impact of fintech on the operations of traditional financial institutions, providing micro-empirical evidence of fintech's ability to alleviate the triangular dilemma of rural credit services. Second, in terms of methods and samples, this paper focuses on the impact of fintech on the operations of rural financial institutions by constructing virtual variables of fintech cooperation and using a multi-period DID model. This not only effectively avoids endogeneity problems but also facilitates the accurate evaluation of the actual effect of cooperation between rural financial institutions and fintech companies. Third, in terms of the research content, this paper enriches the literature on the triangular dilemma in the field of rural finance and provides practical support for rural financial institutions' use of fintech to enhance financial inclusion in the future.

Entrepreneurship not only aids in employment and income growth for farmers but also plays a key role in promoting rural vitalization and assisting farmers and rural areas in achieving common prosperity. While the literature indicates that institutional factors have a significant impact on farmers' entrepreneurship, the specific influence of social credit remains relatively unexplored. In fact, social credit has always played an important role in the economy as an informal institution. Furthermore, with the advancement of information technology and the enhancement of government governance capabilities, social credit, as an informal institution, is undergoing a significant transformation. In 2014, the State Council issued the “Planning Outline for the Construction of a Social Credit System (2014-2020)”, formally incorporating the development of the social credit system into the government governance framework as a systematic project to comprehensively enhance national governance capabilities. In 2022, the General Office of the Central Committee of the Communist Party of China and the General Office of the State Council published the “Opinions on Promoting the High-Quality Development of the Social Credit System to Form a New Development Pattern,” further advocating for the deep integration of credit concepts, credit systems, and credit tools with all aspects and links of the national economic system. The recent document indicates that by utilizing information technology to enhance government governance, the regulatory gap between the informal institution of social credit and formal institutions is gradually narrowing. What are the economic effects of this institutional transition, and how does it affect farmers' entrepreneurship？ Regrettably, these issues still lack sufficient scholarly attention.
Based on data from the China Labor-Force Dynamics Survey, this paper examines the impact of the Construction of China's Social Credit System on farmers' entrepreneurship. It finds that due to information asymmetry, farmers in areas with poorer social credit generally have lower entrepreneurship rates and entrepreneurial status. The public disclosure of dishonesty information effectively alleviates credit information asymmetry, enhances social trust, increases farmers' opportunities to access informal financial resources through “weak ties,” and significantly promotes farmers' entrepreneurship. These positive effects are stronger in less developed regions, and their marginal impact on development-oriented entrepreneurship and the secondary/tertiary sector is pronounced. Further research indicates that compared with local rural farmers, migrant farmers from other regions are more susceptible to external credit conditions due to hukou factors and regional credit disparities.
This paper's innovations and contributions can be summarized in four main aspects. First, this paper breaks the barrier in the literature between work that separately discusses how formal and informal institutions affect farmers' entrepreneurship. It systematically evaluates the economic effects of the transition from the informal institution of social credit to a formal one, offering a new perspective for future research. Second, this paper examines the mechanism of how the construction of a social credit system affects farmers' entrepreneurship from the perspective of the disclosure of dishonesty information, set against the backdrop of increasing rural “atomization” and increasing levels of informatization. It serves as a beneficial supplement to traditional theories on farmers' entrepreneurship. Third, differing from research focused on how social credit affects the efficiency of formal financial resource allocation, this paper finds that the construction of a social credit system also positively affects the efficiency of informal financial resource allocation, thus broadening research in the field of social credit. Fourth, this paper shows that social credit system construction, by establishing a credit information sharing mechanism, compensates for the diminishing “guanxi-based” information sharing mechanism in rural areas under increasing atomization. It effectively alleviates the informal financial resource constraints due to information asymmetry, and it promotes farmers' entrepreneurship. These findings offer new insights that improve the understanding of the effectiveness of social credit system construction and address the challenges of rural entrepreneurship in the new era.
Based on the above conclusions, improving the social credit system, accelerating the construction of the rural credit system, improving rural inclusive finance, and thereby fully utilizing the complementary roles of informal and formal finance are important measures for promoting rural entrepreneurship and stimulating rural economic vitality.

The 2008 global financial crisis underscores the risks of high macroeconomic leverage and highlights the classic credit-driven financial cycle theories of Kindleberger (1978) and Minsky (1977), fueling extensive theoretical and empirical research post-crisis (Eggertsson and Krugman, 2012; Schularick and Taylor, 2012). Concurrently, China witnessed a significant rise in its macro leverage ratio, drawing concentrated policy attention. In 2015, China embarked on a deleveraging policy, and in recent years, it has implemented a series of measures to curb the growth of leverage. However, stimulus policies due to the COVID-19 pandemic in 2020 have reignited concerns about macro leverage risks. Global liquidity stimulus policies increase macro leverage ratios, raising a critical, unresolved question about their impact on the global economy.
The core of credit-driven financial cycle theory pertains to the excessive flow of credit from the financial sector to non-financial sectors, creating investment surpluses and asset bubbles. This illusory prosperity fails to generate real output, leading to defaults, asset crashes, and economic downturns through Fisher's (1933) debt-deflation mechanism. The theory predicts that credit supply-induced increases in the macro leverage ratio (credit stock/total output) result in reduced future output. Although the literature confirms a negative relationship between macro leverage and future total output, it fails to establish causality, making it unable to provide credible validation of debt-driven financial cycle theory. Understanding the dynamics of changes in leverage is crucial for devising precise macro leverage management policies. The key mechanism of debt-driven financial cycles is excessive credit supply, marking supply-side-driven leverage changes as particularly hazardous. Accurately identifying supply-side credit effects on future output is vital for optimal macro policy decisions. In this study, we manually collect a novel cross-country dataset (from the Bank Lending Survey), covering quarterly data for 42 countries from 1994 to 2019. We utilize bank lending standards to measure credit supply directly, retest credit cycle theory, and offer policy insights for emerging markets such as China. All of this work has important theoretical value and practical significance.
First, using the standard two-stage least squares method, we assess how supply-driven sectoral leverage influences total output. We note that a 1% increase in private sector macro leverage due to relaxed credit standards leads to a 0.23%-0.43% decline in total output growth over the next year, with a 5-year average reduction of about 0.15%. Second, by differentiating between the corporate and household sectors, our results show that an increase in non-financial corporate leverage driven by credit supply reduces future total output growth, while household leverage affects economic growth positively in the short term but negatively in the long term. These findings persist even when cyclical factors in credit standards are considered. Third, our findings indicate that stimulative policies, such as the aggregate monetary policy, do not directly lead to sectoral leverage increases or negatively affect future total output growth, thus mitigating concerns about leverage changes due to countercyclical stimulus policies. Lastly, distinguishing between developed and emerging market economies, we observe that in emerging markets, a rapid increase in non-financial corporate sector leverage significantly and persistently dampens total output growth, indicating potential biases if macro leverage management policies in emerging markets directly draw from findings based on developed economy samples.
We make three key contributions. First, we systematically compile Bank Lending Survey data from 42 countries, detailing information such as credit standards for effective use in academic and policy research and thereby enriching the literature on banking and credit. Second, we effectively address the prominent endogeneity issues in the credit cycle literature, providing more reliable validation of debt-driven financial cycle theory. Finally, our findings emphasize the need to maintain stable credit standards and supplies for economic stability, particularly alerting emerging economies to the risks of rapid leverage increases driven by corporate sector credit. In summary, our conclusions provide credible insights for leverage management policies, particularly in emerging market countries such as China.