China's economy continues to face substantial downward pressure. In this context, the 2024 Central Economic Work Conference emphasized the importance of implementing a “moderately loose monetary policy,” while identifying “vigorously boost consumption, enhance investment efficiency, and comprehensively expand domestic demand” as the primary objectives of future economic planning. One of the primary objectives of monetary policy is to promote economic growth, with investment and consumption serving as the key drivers of this growth. Therefore, it is essential to ensure the effective of the monetary policy transmission mechanism in order to maximize the effectiveness of a moderately loose policy in stimulating consumption.
In recent years, China's interest rate liberalization reforms have progressed steadily, facilitating the relatively smooth transmission of monetary policy from intermediate targets to market interest rates. However, the transmission of market interest rates to the real economy has mainly occurred through corporate investment, whereas the transmission effect via household consumption remains underdeveloped. The transmission of market interest rates to consumption has been heavily dependent on traditional banks, which determine how policy rate information is conveyed to deposit and loan rates. This process demonstrates a degree of rigidity: on the deposit side, traditional banks typically leverage their strong market position to keep deposit rates as stable as possible, ensuring the stability of their funding sources. On the loan side, banks' consumer credit marketing practices often lead customers to overlook loan rate information. This situation results in low public awareness of changes in market interest rates, which may constrain the effectiveness of monetary policy transmission.
The rapid development of FinTech enables households to easily access a wide range of products on major tech platforms, enhancing the accessibility and convenience of financial services. Compared to traditional banking products, FinTech offerings face greater competition and more efficient pricing, which allows interest rates to more accurately reflect market rates. Consequently, FinTech adoption may increase residents' sensitivity to market interest rates, enhancing the efficiency of their transmission to household consumption. From this perspective, does FinTech facilitate the transmission of monetary policy to consumption？ If so, what is the underlying transmission mechanism？ Clarifying these questions holds substantial theoretical value and policy implications for improving the efficiency of China's monetary policy transmission.
Therefore, building on Aiyagari's (1994) household consumption decision model, this paper integrates FinTech factors to capture household sensitivity to market interest rates. This clarifies the theoretical mechanism by which FinTech facilitates the transmission of monetary policy to consumption. Furthermore, using Ant Group's micro-level dataset, we empirically investigate the impact of FinTech on the transmission of monetary policy to consumption.
This study draws the following main conclusions: First, frequent use of FinTech products amplifies the impact of accommodative monetary policy on consumption. This suggests that FinTech reduces frictions in interest rate transmission, enhances sensitivity to market rate changes, and strengthens the direct impact of monetary policy on consumption. Second, frequent use of a FinTech platform's digital asset products increases consumption by reducing digital savings under accommodative monetary policy, indicating that the policy operates through the savings substitution channel. Third, frequent use of a FinTech platform's digital credit products boosts consumption by expanding digital consumer credit under accommodative monetary policy. This evidence suggests that monetary policy influences consumption through the credit cost channel, which exhibits asymmetric effects.
This paper makes three primary contributions. First, it analyzes the direct effect of monetary policy on household consumption, emphasizing FinTech's role in enhancing market interest rate transmission and deepening our understanding of its impact. Second, it integrates FinTech's impact on household interest rate sensitivity into a benchmark consumption model, providing a flexible framework for future research on FinTech's influence on household decisions. Third, it uses unique micro-panel data from Ant Group to investigate how FinTech enhances transmission of the monetary policy to consumption, providing micro-level evidence of FinTech's role in macroeconomic regulation and contributing to the development of a theoretical framework for FinTech-enabled macroeconomic policy in China.

The Central Financial Work Conference in 2023 emphasized advancing five key areas: technology finance, green finance, inclusive finance, pension finance, and digital finance. Among these, inclusive finance serves as a critical tool for achieving common prosperity. Proposed by the United Nations in 2005, Inclusive Finance aims to ensure equitable access to financial services for all. With the rapid advancement of digital technology, digital finance has emerged as a pivotal driver in promoting inclusive finance. China is likely to be the leader of the inclusive finance practices.
However, the “Digital Divide” remains a pressing challenge. Based on financial exclusion or credit constraint hypotheses, even if digital technology mitigates collateral deficiencies, resource-constrained low-income households may still face constraint. From a “coverage” perspective, data from the 2019 China Household Finance Survey (CHFS) reveals that only 58.3% of households held third-party digital payment accounts (including internet/mobile payments), rising to 69.5% by 2021. Yet, 40.3% of these accounts had zero balances in 2021, increasing to 43% in 2023. Only 1.1% of households utilized internet loans in 2021, with marginal growth by 2023. The Enterprise Survey for Innovation and Entrepreneurship in China (ESIEC) indicates that 28% of SMEs did not adopt digital payments for procurement, 35% for sales, and less than 6% for payroll, while digital financial borrowing remained limited to 10% in year 2021. Furthermore, the Peking University Digital Finance Inclusive Finance Index shows rapid growth until 2020, followed by a decline to pre-2019 levels post-2021. On the “quality” front, digital inclusive finance faces issues like fraud, asymmetric information, and regulatory gaps. Vulnerable groups lacking digital literacy or computational skills risk insufficient benefits and marginalization despite internet access. Thus, critical questions persist: At what stage is China's digital finance inclusivity？ What barriers hinder its advancement？ This study addresses these gaps through empirical analysis.
Using the micro-data from China Household Finance Survey (CHFS 2017-2019), this paper firstly explores digital financial market participation from the perspective of household wealth disparity, providing new evidence for the development of digital finance participation. Results show that lower-wealth households are significantly less likely to enter digital finance markets (online shopping payments, digital investment and credit) than higher-wealth household. The reason is that for low-wealth families, the entry threshold and financial constraints to enter the digital financial market are significantly higher, including digital financial knowledge threshold, equipment threshold, data flow investment and financial constraints. In addition, the evidence of this paper is more inclined to demonstrate that low-wealth families are mainly self-restraint when entering the digital financial market. On the other hand, wealthy families pay more attention to the factors on the digital supply side. The results are still robust after using instrumental variable method, panel fixed effect and multiple threshold standards. The conclusions show that digital finance still cannot completely go beyond the nature of finance and reach all low-wealth families.
The objective of this paper is not only to examine the impact of household wealth disparities on the constraints of digital finance, but more critically, to uncover the underlying drivers of the barriers hindering the development of digital inclusive finance. By analyzing from the dual dimensions of service breadth and depth, it aims to explore China's practical experience in addressing the challenges of inclusive finance development. This study seeks to provide micro-level household empirical evidence for a more prudent and precise understanding of the concept of digital inclusive finance.
This research yields two key policy implications. First, by advancing technological innovation, upgrading infrastructure, and promoting digital literacy, we can further enhance the accessibility and affordability of digital finance, thereby expanding the breadth of financial inclusion services. Second, regulatory priorities for the digital finance market should focus on regulating market activities, strengthening data security, and other related areas to ensure that suppliers in the digital finance market operate in a healthy, orderly, and standardized manner. By ensuring compliance in the operations of digital finance suppliers, improving the service quality of digital financial products, deepening the depth of inclusive financial services, and encouraging broader participation from wealthier households in the digital finance market, we can ultimately promote the development of inclusive finance.
This paper may engage with and contribute to the literature of following fields.
Theoretically, our results show that the financial constraints hypothesis exists in the digital finance market. This paper compares the differences in household wealth distribution between participants and non-participants of digital finance, examines the exclusionary characteristics of digital finance, verifies whether digital finance has achieved full inclusivity, and explores the underlying drivers of barriers preventing households across different wealth strata from participating in digital finance markets.
Empirically, by differentiating the impacts of digital payment, digital investment, and digital credit on households and employing the instrumental variable approach, it accurately establish the causal relationship between household wealth and digital finance, as well as analyze the underlying mechanisms.
Moreover, the paper attempts to disentangle the digital finance constraints faced by households from both demand-side and supply-side.Specifically, the demand-side factors include digital knowledge or market access thresholds and funding constraints, and supply-side factors include data security, and attributes of digital financial products. This not only serves as an important supplement to existing literature on financial constraints but also holds practical significance, providing reference for policy making by relevant authorities.

The growth of non-tax revenue, increasing debt risks, and the manipulation of fiscal statistics at the local governments have long been the focus of intense debate in China. For example, the National Audit Office reported that 70 local jurisdictions overstated fiscal revenues by 86.13 billion yuan in 2022. In addition, the share of non-tax revenue in general budget revenue rose from 11.05 percent in the first quarter of 2009 to 20.36 percent by the fourth quarter of 2024.
A large body of literature explains these behaviors of local governments from the perspectives of fiscal pressure and GDP promotion tournaments. Notably, since the Reform and Opening-up policy, most practices of the planned economy have been abolished. However, the system of fiscal revenue growth target (Henceforth, FRGT) has been largely retained and, together with GDP and other economic growth targets, continues to serve as a central instrument in implementing China's development strategies across different stages. According to the Budget Law of the People's Republic of China (2018 Revision), governments at all levels announce their annual FRGT at the beginning of each year to the People's Congress. After that, the FRGT is transmitted to local tax collection agencies, where it becomes their mandatory objective. Departments that meet or exceed their targets may receive financial rewards and career promotion opportunities, whereas failure to achieve them can result in both economic penalties and the dismissal of department heads.
FRGT functions as an incentive mechanism within China's multi-tiered government system. While the central government primarily uses FRGT to secure stable funding for its functions, local governments also treat them as a signal of administrative competence. The combination of a complex administrative hierarchy, numerous local jurisdictions, and intricate fiscal information makes it difficult for higher-level authorities to fully monitor compliance. As a result, local governments are both motivated and positioned to engage in strategic revenue management.
Utilizing prefecture-level panel data from 2011 to 2020, this study empirically investigates the impact of FRGT on local government financing strategies. The results show that there is a significant increase in the share of non-tax revenue and local taxes. Revenues from state-owned capital operations and the revenue from the compensated use of state-owned resources and assets respond more strongly to FRGT. Surprisingly, in regions with lower dependence on transfer payments and better economic and fiscal conditions, the responses are more pronounced. Moreover, heterogeneity in legal institutional quality and state capital endowments contributes to regional variation in responses. Bunching estimates further reveal that 10.65% of the sample exhibits signs of strategic data manipulation around FRGT. Further analysis reveals that issues such as subsidies are crucial for understanding the relationship between FRGT and local government revenue management strategies. Finally, empirical evidence suggests an asymmetric response of government expenditure categories to fiscal revenue growth targets, a pattern that merits attention and further investigation.
These findings have important implications for the reform of China's fiscal system. Firstly, reducing the emphasis on FRGT in performance evaluations could shift incentives toward greater fiscal transparency and sustainability, mitigating distortions caused by an excessive focus on revenue collection. Secondly, reforming local governments' command-driven approach to tax collection and strengthening auditing and oversight would promote rule-based, standardized administration. This reform would also reduce the workload of lower-level agencies and foster a more transparent business environment. Thirdly, as reforms of the intergovernmental fiscal system advance, policymakers should consider how local governments respond to institutional changes. They should also strengthen communication and coordination mechanisms and balance centralization with decentralization to guide local authorities toward improving the efficiency and quality of public service delivery.
The potential contributions of this study are threefold. Firstly, it clarifies the theoretical mechanisms through which FRGT influences local governments' strategic revenue management. Secondly, by compiling detailed fiscal data at the prefecture level, the study systematically distinguishes and empirically identifies collection strategies across taxes and non-tax revenues, within different non-tax categories and different tax categories, revealing several key patterns that go beyond prior expectations. Thirdly, it applies a Bunching estimation strategy to directly quantify the extent of revenue overstatement under the fiscal revenue growth target system and to identify the primary operational methods employed by local governments, along with their corresponding consequences.

The 20th National Congress of the Communist Party of China outlined clear plans for improving the multi-tiered social security system and implementing a national strategy to actively address population aging. Currently, China faces a severe aging population issue. In 2023, the number of people aged 60 and above exceeded 290 million, accounting for 21.1% of the total population. Among them, the proportion of elderly individuals with functional impairment or cognitive disorders stood at 11.6%, amounting to approximately 35 million. Population aging is also accompanied by sub-replacement fertility, with China's total fertility rate dropping to just 1.02 in 2023. The low fertility rate is primarily attributed to high fertility costs, significant parenting pressures, and the considerable burden of elderly care. In households with functionally impaired older adults, the heavy caregiving responsibilities can easily lead to a situation where “one member's disability disrupts the entire household,” thereby affecting the ability to raise the next generation. In response, China established a Long-Term Care Insurance system in 2016. By 2024, the number of participants in the pilot cities had reached 187.8634 million, with 1.4625 million beneficiaries, indicating that the implementation of the Long-Term Care Insurance system has achieved initial success. It effectively alleviates the elderly care burden on families and may consequently influence residents' fertility behavior.
The existing literature generally posits that a well-developed social security system tends to significantly reduce fertility intentions. However, some studies also suggest that subsidized social security policies may have a positive effect on fertility rates. Although Long Term Care Insurance (LTCI) shares similarities with other social security policies-as part of the broader social security framework, it may suppress fertility by reducing the perceived old-age support utility of children—its distinctive feature lies in its targeted provision of care services and financial subsidies for functionally impaired elderly. This helps alleviate the burden on families facing the challenge of “one member's disability disrupting the entire household,” thereby reducing the caregiving pressure on family members. Simultaneously, LTCI can indirectly increase household disposable income, enabling a reallocation of family resources from “elderly care” to “childbearing,” which may ultimately enhance fertility rates in families with impaired elderly members. Based on this analysis, this study proposes the following research questions: As a critical initiative in strengthening the social security system, how does the establishment of the Long Term Care Insurance system affect fertility rates？ What is the underlying mechanism？
The main research findings of this paper are as follows: (1) Theoretical analysis indicates that Long-Term Care Insurance (LTCI) suppresses fertility rates in both non-disabled and disabled families by reducing the old-age security utility of “raising children to prepare for old age.” However, LTCI can also enhance fertility in disabled households through a resource reallocation effect. (2) Empirical findings reveal that LTCI inhibits fertility rate in non-disabled families, with this negative effect being more pronounced among high-income households, families with better access to healthcare, and urban rather than rural households. (3) The net effect of LTCI on fertility rate in disabled families is positive, meaning it contributes to an increase in fertility rates. (4) Extended analysis shows that adopting a care model that integrates family-provided care and formal care services helps improve fertility rates in both types of families.
The marginal contributions of this study are as follows: (1) This paper introduces the resource reallocation effect of Long-Term Care Insurance (LTCI) as a novel mechanism and develops a theoretical model illustrating how LTCI influences fertility rates through both the old-age security utility of raising children and the resource reallocation effect. The core distinction between LTCI and traditional social security lies in its provision of professional nursing services, which effectively alleviates the care burden on families with disabled elderly members. This enables the reallocation of household resources from elderly care to childbearing, thereby potentially increasing fertility rates in such families. (2) This study is the first to systematically examine the impact of LTCI on fertility rates from the perspective of its implementation, categorizing households into non-disabled and disabled families for both theoretical and empirical analysis. Furthermore, it incorporates family-provided care as a moderating variable to explore whether an integrated model combining family care and formal care services can mitigate the potential adverse effects of LTCI on fertility rates. The findings aim to provide new policy insights for the sustainable development of the social security system.
The policy suggestions are as follows: (1) The government should expand the coverage of Long-Term Care Insurance (LTCI) and increase the supply of formal care services, with particular emphasis on strengthening formal care security in rural areas. As of June 2024, there were only 16,000 nursing homes in rural China, reflecting a severe shortage of elderly care services. Therefore, the LTCI system should be gradually extended from urban pilot areas to rural pilot regions, accompanied by efforts to increase the number of rural care institutions, diversify service offerings, and enhance the professional skills and service quality of caregivers. These measures would help address the elderly care challenges faced by families with disabled members in rural areas. (2) The government could further optimize the LTCI system by adopting an integrated development model that combines family-provided care and formal care services, thereby improving residents' fertility rates and enhancing the sustainability of the social security system. In practice, several cities have already innovatively implemented such integrated models. For example, Wenzhou allows relatives to provide nursing services; Tianjin offers subsidies and professional training for family caregivers; and the Dongying Branch of China Life Insurance Company Limited promotes a model of “home-based care by relatives with on-site guidance from institutions.” (3) The government should supplement the establishment of a robust social security system with supportive policies such as childcare services and fertility subsidies. Specifically, measures including increasing fertility subsidies, expanding the supply of affordable childcare services, and extending marriage and maternity leaves could help reduce the costs associated with childbirth and child-rearing.

With the continuous improvement of China's environmental governance system, environmental regulations have been significantly strengthened. The implementation of the new Environmental Protection Law (EPL) in 2015, often cited as the most stringent in China's history, imposed stringent compliance requirements on firms. The new EPL focused on strengthening regulatory responsibility, increasing penalties, and enhancing public supervision. Violations could lead to severe punishments, raising environmental uncertainty for firms, and heavily polluting enterprises were expected to face greater compliance costs. This policy shift rendered the previous high-leverage, high-emission business model of heavily polluting firms unsustainable, exposing them to heightened environmental risks. We examine whether and how these firms adjust their capital structure in response to the heightened regulatory uncertainty. Employing a difference-in-differences (DID) design and data from Shanghai and Shenzhen A-share listed firms (2007-2023), we exploit the implementation of the new EPL as a quasi-natural experiment to identify its causal effect.
We find that the new EPL significantly reduced the asset-liability ratio of heavily polluting firms, primarily driven by a decrease in interest-bearing debt. Compared to non-heavily polluting firms, the implementation of the new EPL had a significant negative impact on the asset-liability ratio of heavily polluting firms, which decreased by 2.4% relative to non-heavily polluting firms after the implementation. Furthermore, the reduction effect of the new EPL on the asset-liability ratio of heavily polluting firms mainly came from the decrease in the interest-bearing debt ratio.
In addition, the impact of the new EPL on capital structure varies across different types of firms. The reduction effect is more pronounced among firms with lower levels of environmental information disclosure, weaker financing constraints, and those that are not major taxpayers.
Mechanism tests explain how environmental regulations affect the capital structure adjustments of heavily polluting firms through changes in environmental risk. The new EPL set stricter compliance standards, increasing environmental uncertainty for heavily polluting firms. If these firms continued to use the high-leverage, extensive operational model, they would face violation penalties and high compliance costs. Consequently, firms actively engaged in environmental management to meet new emission standards and regulatory requirements, including increasing green investment and reducing production scale. These activities compressed short-term profitability, increased financial pressure, and raised operational uncertainty, thereby motivating firms to lower leverage for financial stability. First, using text analysis of annual reports, we constructed a dictionary from three dimensions, environmental and climate risk, regulatory perception, and green transition, to capture semantic features related to environmental risk, and calculated the word frequency of environmental risk keywords in annual reports based on this dictionary. The study finds that heavily polluting firms significantly increased the frequency of terms related to environmental uncertainty in their annual reports after the implementation of the new EPL, indicating that these firms conveyed an increased perception of environmental risks through textual information disclosure and had heightened psychological expectations of future environmental compliance and penalty risks. Firms that perceive increased environmental risks adopt compliant behaviors in response to stricter environmental regulations, manifested in the new EPL's effect through increased environmental investment and reduced production scale.
We also explore the impact of the new EPL on trade credit. Further analysis shows that the new EPL also led to an increase in the net use of trade credit. This indicates that after the rise in environmental risk, in addition to adjusting their capital structure, firms also utilized their bargaining power in the supply chain to increase cash reserves and enhance liquidity management capabilities. Furthermore, firms reduced new bank borrowing and increased equity financing to improve their situation and maintain financial stability.
Our findings contribute to the literature on the micro-level impact of environmental regulation. While prior studies focus primarily on environmental governance practices and environmental performance, we highlight how firms adjust financial structures under regulatory stringency. By examining capital structure responses to an exogenous policy shock, this study broadens the understanding of the economic and financial consequences of environmental policy.
Moreover, this research contributes to the literature on risk and capital structure. Existing studies seldom examine the transmission mechanisms of environmental compliance risk. By testing how policy-induced risks are internalized into financing decisions, this study extends risk-related research into the domain of command-and-control environmental regulations, offering a novel perspective on how firms adjust risk in response to regulatory shocks, thereby enriching the theoretical foundation of environmental regulation and providing new insights for understanding and managing environmental risk in the process of green transition.

Environmental, Social, and Governance (ESG) has become a critical indicator for assessing corporate sustainable development ability. Investors and regulators increasingly rely on third-party information channels, such as media coverage and ESG ratings, to compensate for deficiencies in corporate ESG disclosure. Compared with ESG ratings, which often suffer from time lags and oversimplification, media reports are more timely and richer in content. However, they also inevitably contain subjective judgments and emotional tones introduced by journalists and editors. This dual nature grants ESG news sentiment both an “information transmission” and an “emotional contagion” function in capital markets, making its impact on corporate investment decisions and underlying mechanisms a meaningful academic issue.
Drawing on corporate governance theory and behavioral finance theory, this study develops a dual-path “information-emotion” analytical framework to examine the effect of ESG news sentiment on corporate inefficient investment. From the perspective of corporate governance, information asymmetry and agency problems are key drivers of inefficient investment; from the perspective of behavioral finance, investor and managerial sentiment may also distort investment decisions. Based on these theoretical underpinnings, two pathways are proposed: (1) the information effect, whereby ESG news sentiment mitigates information asymmetry, improves financing conditions, and strengthens monitoring mechanisms, thereby restraining inefficient investment; and (2) the emotion effect, whereby the timeliness and narrative features of ESG news amplify market optimism and managerial cognitive bias, leading to investment expansion and intensified inefficiency. While these two effects may theoretically offset each other, in practice the emotional effect tends to dominate due to its immediacy, contagion, amplification, and accumulation.
To test the theoretical framework, this study uses a sample of China Shanghai and Shenzhen A-share listed firms from 2013 to 2023. ESG news sentiment scores are obtained from the Datago ESG News Quantitative Sentiment Database, and combined with financial data and indicators of inefficient investment for empirical analysis. The findings are as follows: (1) Overall, ESG news sentiment is significantly and positively associated with corporate inefficient investment, indicating that more favorable sentiment intensifies inefficient investment. This result holds under various robustness checks. (2) Mechanism analysis reveals that the information effect reduces inefficient investment by alleviating information asymmetry, whereas the emotional effect exacerbates inefficiency by stimulating investor sentiment and managerial optimism. Specifically, ESG news sentiment does not induce managerial opportunistic behavior but primarily operates through cognitive bias. (3) Sub-dimension analysis shows that governance-related news sentiment has the strongest effect, highlighting the close linkage between governance issues and investment efficiency. (4) The intensifying effect of ESG news sentiment on inefficient investment is more pronounced in non-state-owned enterprises, capital-intensive industries, firms with weaker organizational inertia, managers with higher risk preference, and in environments with weaker market constraints (e.g., lower analyst coverage and reduced short-selling pressure).
This study makes three key contributions to the literature. First, at the theoretical level, it innovatively incorporates ESG news sentiment into the framework of inefficient investment research, proposing and validating the dual-path “information-emotion” mechanism. This approach advances beyond prior studies that treated ESG as a uniformly positive factor and uncovers its “double-edged sword” role in capital markets. Second, from a research perspective, this study differentiates itself from broader media sentiment research by focusing specifically on ESG-related news, a subset of soft information, and by distinguishing between the mechanisms of information transmission and emotional contagion, In doing so, it provides new empirical evidence for understanding the role of media sentiment in investment decision-making. Third, at the practical level, the findings offer implications for regulators, firms, and investors. Regulators should promote standardized ESG disclosure, enhance media oversight, and establish sentiment governance mechanisms to prevent emotion-driven investment distortions; firms should avoid catering to short-term sentiment, strengthen governance capacity, and pursue rational decision-making; investors should remain vigilant against amplified sentiment effects and make prudent investment decisions based on fundamentals to avoid misjudging firm value amid market fluctuations.

The Third Plenary Session of the 20th Central Committee of the Communist Party of China emphasized improving the Party and state's supervisory system and enhancing the quality of listed companies. As a key component of this system, government accounting supervision, which is led by the Ministry of Finance (MOF), aims to improve the quality of financial reporting. While previous studies have mostly focused on its direct effects on inspected firms, this paper explores whether such supervision can also strengthen the external monitoring role of financial intermediaries, particularly analysts.
Analysts play a vital role in reallocating investor attention and enforcing market discipline by producing forecasts and research reports. High-quality analyst forecasts reflect stronger external governance and are aligned with efforts to improve forecast reliability. As the MOF has increasingly adopted random inspections of accounting information quality, a natural question arises: Can such inspections enhance analyst forecast quality and thereby foster supervisory synergy？
We propose that MOF random inspections improve analyst forecast quality through two mechanisms: (1) enhancing the accounting information quality of inspected firms, (2) increasing the precision of public information. The MOF, by conducting audits, enforcing accountability, and promoting corrective actions, helps standardize corporate reporting, strengthen internal controls, and reduce future regulatory risks. As an independent regulator, the MOF produces information that is credible, low-cost, and publicly accessible, thereby improving the overall information environment and reducing asymmetry to benefit analysts.
Using a difference-in-differences design, we examine the impact of MOF inspections on analyst forecast quality. We manually collect inspection data from MOF announcements and supplement it with disclosures from stock exchanges and industry sources, identifying 303 listed firms subject to inspections from 2007 to 2023. After excluding firms with missing or abnormal data, we find that following public disclosure of inspection results, analyst forecast accuracy improves by 2.81%, optimism bias declines by 10.52%, and forecast dispersion decreases by 5.46%. These findings remain robust across multiple empirical checks.
Mechanism tests confirm that the improvements in both financial reporting quality and public information precision mediate the observed effects. The impact is more pronounced among firms with more serious accounting violations, detailed inspection disclosures, strong rectification responses, non-state ownership, and lower audit quality. These results demonstrate that MOF inspections not only improve internal reporting but also activate the external oversight function of analysts, forming a coordinated supervisory effect.
Policy implications are threefold. First, the MOF should continue to play a leading role in joint supervision, fostering coordination with analysts, auditors, and professional associations to build a collaborative oversight system. Second, local fiscal authorities should leverage big data and AI to identify high-risk firms for targeted inspections. Third, MOF inspection announcements should be standardized and enriched with detailed findings to enhance their transparency and usability.
This study enriches our understanding of how government-led supervision can influence financial intermediaries and contribute to broader governance outcomes. Future research may explore additional outcomes, such as effects on earnings management or spillovers to other stakeholders, including suppliers and auditors.

Dividend tax is a core tax category levied on capital income within the framework of individual income tax, occupying a significant position in the current tax structure of China. However, there has been a long-standing debate over how dividends should be taxed, as it involves a stark equity-efficiency trade-off. On the one hand, property income such as dividends, accounts for a large portion of the income of high-income groups. Taxing dividends could help regulate income distribution. On the other hand, dividend taxation may lead to substantial efficiency losses, primarily manifested in investment. Since investors' net returns were reduced, dividend taxes may reduce investment and distort resource allocation. In view of this trade-off, it is essential to know the impact of dividend taxation on corporate behavior, especially on corporate investment behavior. However, how dividend taxation affects companies' real activities has been controversial in public finance. What exactly is the impact of dividend tax rate changes on the investment behavior of Chinese firms？ This remains an open empirical question.
This paper investigates this issue by examining the differentiated dividend tax reform implemented in China in 2013. Prior to the reform, individual investors of listed firms were subject to a uniform dividend tax rate of 10%. In this reform, however, China linked the dividend tax rate for individual investors to the duration of their shareholding, raising the dividend tax rate for short-term investments within one month and lowering the dividend tax rate for long-term investments over one year. As a result, although all listed firms were affected by the reform, the extent of the impact varied between firms with different investor structures, which allows us to employ a continuous difference-in-difference method to identify the causal relationship between dividend tax and corporate investment strategies. Using China A-share listed firms from 2011-2015 as the sample, this paper finds that changes in dividend taxes do not have a significant impact on firms' average investment. However, listed firms exhibit heterogeneous investment responses to an increase in dividend tax rate based on their varying levels of cash abundance. A higher dividend tax rate exacerbates the agency problem between managers and shareholders, leading to more unproductive investments by cash-rich firms. At the same time, cash-constrained firms reduce productive investments due to the rising cost of capital. This means that higher dividend tax rates lead to a shift in investment from higher-return investments in cash-constrained firms to lower-return investments in cash-rich firms, thereby reducing the efficiency of resource allocation.
The research findings in this paper have important implications for deepening tax system reform and optimizing investment structure. Noting that dividend tax is a crucial factor affecting investment structure and efficiency, the appropriate reduction of dividend tax rates, coupled with the coordination and integration of corporate income tax and individual income tax, would represent crucial tax reform directions that effectively balance high-quality development and common prosperity.
Possible contributions of this article are as follows. First, in terms of research perspective, while some literature has discussed the impact of China's differentiated dividend tax policy on other behavioral decisions such as corporate payout policies, no study has separately examined its effect on corporate investment decisions. This study contributes to a deeper understanding of the policy effects of China's dividend tax reform, which is of great importance for the improvement of China's tax system. Second, in terms of empirical identification, the differentiated dividend tax reform results in different investors' average dividend tax rates for listed firms with different investor structures, forming a natural grouping. This enables us to only use data from listed firms while identifying the impact of dividend tax on corporate investment, avoiding potential endogeneity issues that may arise when using firms with different organizational forms (e.g. non-listed firms) as the control groups, which thereby enhances the reliability of research conclusions. Third, in terms of content, this study examines the impact of dividend tax on corporate average investment, investment allocation, and investment efficiency under a new scenario of China, a developing country, providing new insights into the ongoing debate surrounding dividend tax. Moreover, unlike recent literature that primarily focuses on non-listed firms, this study addresses the issue within the sample of modern listed firms, where agency conflicts are more pronounced due to diffuse ownership. This should help deepen the understanding of the investment effect of dividend taxation in academia.

Standards are an important aspect of the country's basic system, and standard guidance is an important symbol for an economy to enter high-quality development and participate in high-quality competition. Fully exploring the economic efficacy of standardization efforts to clarify the underlying mechanism through which standardization promotes high-quality development has become an important issue. It has been confirmed that standardization exerts a profound impact on the vitality and efficiency of commodity markets and factor markets. However, no research has systematically examined the influence of standardization on capital market efficiency. To fill this gap, this study investigates the impact of enterprise standardization on stock liquidity.
This study analyzes the effect of enterprise standardization on stock liquidity through two channels: market competitiveness and information asymmetry. First, standardization facilitates product quality control, promotes innovation, drives enterprises toward lean management, and enhances labor productivity. These improvements strengthen corporate market competitiveness, thereby improving stock liquidity. Second, as an effective supplement to enterprises' explicit information, the disclosure of standard-related information enables investors to gain a better understanding of enterprises' production process, technical applications, workflow characteristics, and other aspects, which effectively expands the information set available for investors' decision-making, alleviating information asymmetry and improving stock liquidity.
We manually collect the standardization information of listed companies. We find that a one-standard-deviation increase in the level of enterprise standardization leads to an average 4.42% increase in corporate stock liquidity, indicating that standardization has a significant positive effect on stock liquidity. The underlying mechanism lies in enhancing corporate market competitiveness and alleviating corporate information asymmetry. Cross-sectional analyses show that the impact of enterprise standardization on stock liquidity is more pronounced in regions with higher judicial quality because high-quality judicial systems ensure the effective enforcement of standards, thereby allowing standardization to better fulfill its role. Moreover, compared with standardization at the national, local, and industry levels, standardization at the enterprise and group levels has a more significant effect on stock liquidity. Compared with work standardization, technical standardization, and management standardization have a more significant effect on stock liquidity. Finally, the analysis of economic consequences shows that enterprise standardization can significantly reduce enterprise default risk by improving stock liquidity.
This study makes three possible contributions.First, further stimulate the vitality of market entities in standardization. Continue to promote the market-oriented transformation of the standard supply mechanism, enhance the participation and voice of market entities in standard-setting, and improve the adaptability and scientificity of the standard system. Second, promote the coordinated development of standardization and scientific and technological innovation. Further explore the linkage mechanism between scientific and technological innovation and standardization work, such as incorporating standard-setting into the outcome requirements of scientific and technological innovation projects, and focusing on providing standards in key technology fields. Third, improve the level of openness and sharing of standard information. Enterprises should enhance the openness of standardization and realize interconnection and sharing of standard information in a wider scope. Fourth, strengthen standard implementation and judicial protection. Incorporate enterprises’ standard implementation status into the social credit system, and strengthen the in-process and post-implementation supervision of standard enforcement. Through a combination of incentives and constraints, the actual implementation effect of standards could be improved. Finally, enhance the applicability of enterprise standards and association standards. When formulating internal standards, enterprises should align with their own development stage and business characteristics, focus on the coordination between the standard system, corporate strategy and organizational culture, avoid being divorced from reality and becoming a mere formality, and effectively let standards play a role in improving operational quality and efficiency.

Recognizing, distinguishing, and characterizing the heterogeneous features of micro-level agents constitutes the foundation for advancing micro-level regulatory technologies and constructing a capital market theory grounded in heterogeneous agent behavior. From the practical perspective of financial risk management, the focus of regulatory issues has shifted from “how to regulate” to “the efficiency of regulatory input and output.” Real-time monitoring of all micro-market participants would result in significant waste of computational resources and diminishing marginal returns from regulatory efforts. From the theoretical perspective of financial risk management, the behavioral characteristics of micro-agents, their heterogeneity, and their interactions represent the underlying drivers of systemic risk emergence within the macro-level capital market as a complex system. Meanwhile, advances in information technology have continuously enhanced the acquisition and analytical capacity for massive micro-level data. The joint forces of technological progress and theoretical demand necessitate deeper academic inquiry into micro-level heterogeneity.
Although prior studies have made certain progress, the simple reliance on “intuitive” classification criteria such as wealth or age has left numerous issues unresolved. The most salient problems include: (i) insignificant differences across categories, (ii) failure to identify critical categories, and (iii) the inability to justify the selection of segmentation boundaries. The first two issues substantially diminish the applicability of classification methods in managerial contexts, whereas the subjectivity in boundary selection severely undermines their generalizability for research applications. Consequently, existing studies primarily examine the impact of predefined labels on investor behavioral heterogeneity rather than exploring how labels can be cut to effectively distinguish investor behaviors, leaving a notable research gap.
Building on the premise that investor types are fundamentally shaped by their behavior, this study employs data from 96,072 individual investor accounts spanning 2016 to 2021, along with 109 stock factors, to classify and analyze investors based on their holding preferences. The results reveal that stock price, as a singular characteristic, emerges as the most significant determinant of internal preference divergence among individual investors, thereby distinguishing distinct investor types in terms of their holdings.
Based on the relative importance of preference divergence and the intercorrelation among indicators, this study ultimately focuses on nine firm characteristics. Employing Principal Component Analysis (PCA) for dimension reduction, we summarize the major sources of heterogeneity in investor preferences into two composite dimensions: price-attention factor and shell-value factor, which collectively explain over 50% of the overall heterogeneity across the nine indicators. This outcome not only aligns with existing asset pricing and individual investor studies in the Chinese market but also corroborates the widely cited retail investor adage: “Bet on restructuring (shell value) mid-year and on earnings (low price and low attention) at year-end.”
Subsequently, using each investor's positions along these two composite dimensions, we apply the K-means clustering algorithm to categorize investors and examine the relationship between preference-based clusters and investors' demographic and behavioral characteristics. The empirical findings indicate that investor classification derived from stock-holding preferences is not driven by a single demographic label but rather by a combination of multiple attributes and behavioral patterns. For example, two investor clusters may both display characteristics such as a small portfolio size, older age, longer investment experience, lower education, and a lower turnover ratio, making differentiation based on a single demographic label infeasible. However, segmentation based on holding preferences reveals that investors with a strong shell-value orientation warrant closer regulatory attention compared to relatively mature and conservative investors under a tiered supervision framework.
Based on the findings, three policy recommendations are proposed:
First, enhance tiered supervision and risk warning systems. In light of the challenges posed by financial innovation and digitalization, strengthening the regulatory framework requires robust support from supervisory technology (RegTech). Considering the efficiency constraints in comprehensive micro-level financial regulation, we recommend adopting an approach similar to that presented in this study—identifying core investors based on stock-holding preferences to accurately target risk-asset holders and potential spillover agents, and implementing dynamic, tiered regulation.
Second, deliver investor education tailored to heterogeneity. In a market dominated by retail investors—with over 200 million small and medium-sized participants—we recommend using stock-holding preferences as an entry point for investor education. Through regular review and monitoring, regulators can correct behavioral biases, such as excessive risk-seeking and gambling tendencies.
Third, employ shell-value preference as a quantitative indicator to advance the registration-based system. At present, China is implementing institutional reforms on both the asset and investor fronts. To address the difficulty of quantifying policy feedback on the investor side, we suggest leveraging the technical approach outlined in this study to measure shell-value preferences among different investor groups, thereby providing an empirical basis for tracking policy responses and evaluating the effectiveness of reforms.

In recent years, public offering of funds in China has developed rapidly and plays a crucial role in the financial market. As important institutional investors, the behavior of funds can have a significant impact on the correlation between stocks, which is also a key factor in stock pricing and risk. With the continuous expansion of assets under management, the investment behavior of funds may further affect stock prices by influencing the correlation between stocks. A deep understanding and analysis of the relationship between funds and stock price comovement is crucial for the stable development of China's stock market and the safety of the financial system.
Antón and Polk (2014) find that the common ownership of two stocks by US mutual funds significantly increases their future price correlation, enhancing price comovement. This conclusion has also been verified in China. In fact, a network emerges among stocks that are commonly held by funds, which is the fund common ownership network. In this network, where stocks serve as nodes, stocks directly commonly held by funds exhibit comovement. This is akin to the correlation between “neighbors” in the network, representing a first-order network effect, and has been the focus of existing literature. Moreover, different funds often share information on the same large-position stocks, potentially exhibiting a herding effect in asset allocation, and even facing similar fund flow shocks. This leads to correlations in their trading behaviors. Consequently, stocks that are not directly commonly held by funds may also experience indirect price comovement under the influence of the fund common ownership network, representing a higher-order network effect or the influence from multi-layered “neighbors of neighbors”. Existing literature primarily focuses on the correlations between two stocks directly held by funds, neglecting the price comovement within a higher-order network.
Using open-ended active equity funds and their holdings of Shanghai and Shenzhen A-share stocks from 2007 to 2022 as samples, we construct a fund common ownership network with stocks as nodes, and employ a spatial autoregressive model to study the price comovement and risk contagion under this network. We make four main contributions. First, we establish a fund common ownership network based on common shareholding behaviors of funds, enriching the literature related to stock networks. Second, existing literature measures stock price comovement from a correlation perspective, focusing on the similarity between two time series. This approach not only fails to effectively quantify the amplitudes of cross-sectional comovement but also overlooks possible indirect links among a wider range of stocks, which can be solved by a spatial autoregressive model. Third, we analyze how the fund common ownership network influences stock price comovement from three perspectives: fund flows, information sharing, and investor sentiment. Fourth, we show that the fund common ownership network may serve as a contagion channel under extreme market scenarios, through which the suspended stocks can impact unsuspended stocks, thereby enriching the literature on stock market risk contagion.
The research findings indicate that stocks exhibit significant price comovement under the fund common ownership network, supported by a series of robustness tests. We discover that stocks exhibit stronger price comovement effects under networks with higher fund flows and higher information sharing. Furthermore, the higher the investor sentiment, the greater the intensity of stock price comovement within the fund common ownership network. By applying a spatial autoregressive Tobit model to conduct cross-sectional regressions on daily returns during the significant fluctuation in the stock market in 2015, we find that not only do unsuspended stocks exhibit significant price comovement within the fund common ownership network, but large-scale suspended stocks can also impact the prices of unsuspended stocks through this network. Our research points out that the fund common ownership network not only affects stock price comovement but also potentially serves as a channel for risk contagion in extreme events. The conclusions offer insights into the relationship between fund common ownership and stock price comovement, and have implications for preventing risk contagion in the capital market.