Expanding domestic demand serves as the strategic foundation for facilitating the domestic economic cycle, promoting domestic and international dual circulation, consolidating China's advantage of hypermarket, and safeguarding against uncertainties in the external environment. As dual engines for domestic demand expansion, the comprehensive unleashing of consumption potential and the elimination of investment barriers constitute critical components for ensuring the effective implementation of this strategy. However, future inflation expectations are highly uncertain due to the intertwining and interplay of many factors, such as escalating geopolitical risks, disrupted global supply chains, and intensified great-power competition. Economic theory has demonstrated that inflation uncertainty significantly influences consumption behavior and investment decisions of economic agents (Dixit & Pindyck, 1994), implying that such uncertainty inevitably impacts China's domestic demand expansion strategy. Particularly under the current complex and volatile environment, the driving factors of inflation uncertainty and its transmission mechanisms affecting the dual engines of domestic demand-consumption and investment-have become increasingly intricate. This necessitates enhanced precision in identifying inflation uncertainty and evaluating its impact on domestic demand, presenting novel requirements for policy formulation and academic research.
Research Content: First, based on a high-dimensional price index system, this study constructs China's inflation uncertainty index from 2006 to 2022 using a Factor-Augmented Vector Autoregression with Stochastic Volatility (FAVAR-SV) model that incorporates factor volatility characteristics. Second, given the ambiguous nature of inflation uncertainty, we theoretically extend the real options model from known probability measure spaces to unknown probability spaces, exploring the transmission mechanisms and effects of inflation uncertainty on the dual engines of domestic demand—consumption and investment. Finally, drawing on theoretical insights, we employ a Time-Varying Parameter FAVAR (TVP-FAVAR) model to empirically investigate the dynamic impact of China's inflation uncertainty on these dual engines. All raw data utilized in the research are sourced from the WIND database, which is widely adopted by Chinese scholars.
Research Findings: First, the dynamic evolution of inflation uncertainty in China is closely linked to major economic disruptions such as financial crises and the COVID-19 pandemic. Since the outbreak of COVID-19 in 2020, inflation uncertainty has risen significantly without signs of abatement, though it remains lower than during the 2008 global financial crisis. Second, theoretical analysis reveals that the penalty effect and wealth value disturbances serve as transmission mechanisms through which inflation uncertainty influences consumption and investment decisions of economic agents. However, the strength of these transmission effects varies with shifts in macroeconomy. Third, empirical results align with theoretical conclusions. During periods of stable economic growth, the impact of inflation uncertainty on consumption and investment is relatively muted. In contrast, distinct inhibitory effects emerge after financial crises and during the “new normal” of economic development, with a notably intensified suppression effect observed in the post-COVID-19 era.
Policy Implications:First, although China is currently experiencing a low-inflation scenario, the increasingly volatile geopolitical and economic landscape—particularly the intensifying rivalry between China and the U.S. in finance, technology, and trade tariffs—is likely to amplify stochastic information shocks that drive inflation uncertainty. Policymakers should remain vigilant in monitoring the dynamic characteristics of inflation uncertainty. The measurement methodology proposed in this study can be adopted to establish and refine a more sensitive and precise inflation uncertainty monitoring system. Second, regulatory authorities should enhance communication with the public, improving the transparency of macroeconomic policies to guide the formation of rational inflation expectations. This approach would help mitigate economic agents' perceived uncertainty regarding future inflation at its source. Third, the intensity of domestic demand policies should be adjusted flexibly in response to macroeconomic conditions. During major economic disruptions—such as financial crises, the COVID-19 pandemic, and trade disputes—policymakers must ensure the timeliness and potency of demand-stimulating measures. Policy interventions should prioritize stabilizing wealth levels, including maintaining the value of assets such as stocks, bonds, and real estate, to counteract the negative effects of inflation uncertainty on domestic demand.
Research Contributions: First, this study advances the measurement of inflation uncertainty in the existing literature. By employing a FAVAR-SV model capable of accommodating high-dimensional price indicator systems, it addresses the information omission problem inherent in prior studies that rely solely on CPI volatility as a proxy. Furthermore, defining uncertainty through the volatility of latent common factors-which are inherently unobservable-resolves the limitation of GARCH-type models in filtering out predictable components from disturbance terms in price variables. Second, the paper refines the real options model, enhancing its applicability for analyzing economic agents' optimal decision-making under uncertainty shocks. Lastly, the findings not only provide a policy foundation for China's domestic demand expansion strategy but also contribute novel theoretical and empirical evidence to the study of macroeconomic uncertainty in the Chinese context.
Research Prospects: First, the digital economy era presents new opportunities to enhance inflation uncertainty measurement through big data and artificial intelligence, offering a novel methodological approach for more precise monitoring. Second, the heterogeneous impacts of high-, medium-, and low-level inflation uncertainty across regions, firm types, and household demographics constitute important avenues for future investigation.

According to the China Financial Stability Report (2024) released by the People's Bank of China, the corporate sector leverage ratio reached 168.0% at the end of 2023, an increase of 6.1 percentage points from the end of 2022, accounting for 52% of the total rise in the macro leverage ratio. The report suggests that the structure of corporate sector leverage has been improving, contributing positively to the ongoing economic recovery. As China's economic conditions have evolved, the understanding of leverage-related issues has also shifted. While the Central Economic Work Conference in 2015 emphasized “deleveraging”, it was later recognized that excessive deleveraging could trigger balance sheet recession risks and unfavorable for economic growth. In 2019, the Central Economic Work Conference proposed the goal of “maintaining economic performance within a reasonable range and keeping the macro leverage ratio basically stable”, marking a policy shift toward balancing “leverage stability” and “growth stability” as dual objectives. Currently, with China's economy showing steady and positive momentum, maintaining relatively stable or moderately rising corporate leverage may help sustain recovery and growth.
Since the reform of China's exchange rate regime in July 2005, fluctuations in the RMB exchange rate have had a significant impact on the leverage of manufacturing enterprises. During the general appreciation of the RMB's real effective exchange rate, the corporate sector's leverage ratio rose from 99.00% in 2006 to 168.00% in 2023, closely tracking the exchange rate trend. This raises a crucial question: is there a causal relationship between RMB exchange rate movements and corporate leverage？ If so, what are the underlying mechanisms？
This paper addresses these questions through both theoretical modeling and empirical analysis. First, it develops a three-stage decision-making model of firms' debt financing under exchange rate change, demonstrating that exchange rate changes affect leverage through three mechanisms: the innovation effect, the cost-saving effect of imported intermediate goods, and the balance sheet effect. Second, using a panel dataset of Chinese listed manufacturing firms from 2007 to 2016, this study merges customs trade data, CSMAR firm-level data, and IMF-IFS macroeconomic data to empirically test the impact of RMB real effective exchange rate fluctuations on firm leverage. The results show that RMB appreciation increases firm leverage through the innovation and balance sheet effects, while it decreases leverage through the cost-saving effect from imported intermediates. Overall, the positive effects of appreciation on leverage outweigh the negative, leading to a net increase in firm leverage. Further analysis by type of intermediate goods reveals that the cost-saving effect of RMB appreciation is more significant for imported parts and components than for primary intermediates. Heterogeneity tests indicate that the leverage-enhancing effect of RMB appreciation is more pronounced among state-owned enterprises and high-tech firms.
Compared with existing literature, this paper contributes in several ways. (1) Theoretically, it is the first to build a three-stage decision framework from the perspective of firms' production and R&D decisions, where firms sequentially choose optimal debt levels, R&D investment, and product pricing to maximize profits. (2) Empirically, this study identifies that the RMB appreciation influences firm leverage through three mechanisms: innovation effects(positive), balance sheet effects (positive), and the cost-saving effects of imported intermediate goods (negative).
The policy implications of this paper are as follows: First, in light of China's steady economic recovery and the likely future trend of a “stable-to-strong” RMB, moderate increases in firm leverage may be tolerated. It is recommended that policymakers actively support corporate innovation by facilitating access to innovation financing under controllable risk. Empirical results indicate that firms tend to enhance innovation to maintain global competitiveness during RMB appreciation, which typically involves higher leverage. Overemphasis on “deleverage” could inadvertently constrain firm financing and growth.
Second, optimizing the structure of intermediate goods imports—especially by increasing imports of parts and components—could help reduce manufacturing firms' leverage. Results demonstrate that firms can effectively reduce the cost of imports, and hence leverage, by importing intermediate goods when the local currency appreciates. While the cost-saving effect of imported intermediates is generally smaller, the growing role of Chinese firms in global production networks means that importing technologically advanced components can yield greater financial benefits under a stronger RMB. Looking forward, the logic won't change that strong economy is accompanied with strong currency. With the future trend of a “stable-to-strong” RMB, firms could make full use of the cost advantage of importing intermediates, increase imports of intermediate goods and optimize the structure of imported intermediate goods will, to some extent, help to reduce corporate leverage.
Third, as China's trade continues to expand, improving the debt financing environment for manufacturing firms is essential to help them adapt to the future trend of a “stable-to-strong” RMB. Heterogeneity analysis reveals that the leverage-enhancing effect of RMB appreciation is more pronounced among state-owned firms and high-tech firms. Moreover, exchange rate appreciation significantly increases both financial leverage and long-term leverage of firms. These findings suggest that the innovation and balance sheet effects induced by RMB appreciation tend to increase firms' demand for external financing. In response, policymakers should take the opportunity to optimize the financial supply system, enhance the accessibility and inclusiveness of financial services, and foster a favorable debt financing environment.

In August 2020, the People's Bank of China, along with the China Banking and Insurance Regulatory Commission and other institutions, introduced the “Three Red Lines” policy targeting the real estate sector. Subsequently, China's real estate market entered a downward trajectory, leading to a contraction in bank credit. Why did this happen？ This paper analyzes the transmission mechanisms and pathways through which the real estate market adjustment since 2021 has contributed to an overall decline in social investment. Furthermore, it examines the effectiveness of different monetary policy measures and the combined effects of policy interventions.
Empirical evidence reveals that, on one hand, the real estate sector in China is highly intertwined with bank credit. A decline in housing prices leads to a reduction in real estate loans, which, in turn, results in the contraction of commercial banks' balance sheets and a decrease in the scale of credit. On the other hand, falling housing prices lead to a decline in land prices, reducing local government fiscal revenue and subsequently diminishing capital demand from non-real estate sectors. Based on these facts and logical connections, this paper develops a multi-sector dynamic stochastic general equilibrium (DSGE) model that incorporates both real estate and non-real estate sectors. The model introduces local governments to depict land financing behavior and incorporates the banking sector to capture financial frictions. This framework is used to analyze the impact of declining real estate demand on commercial banks' balance sheets, as well as the effectiveness of various policies in improving commercial banks' balance sheets and the broader macroeconomy.
Theoretical model results indicate that, on one hand, a decline in real estate demand leads to a decrease in investment in the real estate sector and a drop in asset prices. On the other hand, falling housing prices result in lower land prices, reducing local government land revenues, which in turn decreases capital demand and asset prices in the non-real estate sector. The decline in asset prices across both sectors leads to a reduction in commercial banks' net worth, thereby constraining their credit supply. If the central bank lowers the reserve requirement ratio (RRR), it can improve commercial banks' balance sheets and enhance credit supply. If the central bank reduces the interest rates on existing housing loans, this could help boost household consumption but may also reduce banks' net worth, further constraining credit supply. In this case, it would be necessary to inject additional capital into commercial banks.
This paper offers the following policy recommendations. First, in the short term, targeted policies should be implemented to improve the balance sheets of commercial banks, while in the long term, efforts should be made to reduce the dependence of commercial banks on the real estate sector. Second, when reducing interest rates on existing housing loans, it is essential to simultaneously inject capital into commercial banks. Third, fiscal and taxation system reforms should be advanced in a coordinated manner to expand local tax sources.
The contributions of this paper are primarily reflected in three aspects. First, although existing literature has explored the connections between the real estate market and commercial banks, the analysis of banks' balance sheets remains insufficient. This paper collects and organizes relevant data to analyze the relationship among the real estate market, commercial banks' balance sheets, and the macroeconomy. It provides a new perspective for understanding the interactions between the real estate market and the financial system, as well as empirical evidence for building theoretical models. Second, previous studies have mostly focused on the crowding-out effect of rising housing prices on the non-real estate sector. However, in the current context of declining housing prices, not only has investment in the non-real estate sector failed to improve, but the overall scale of social credit has also declined. Following Gertler and Karadi (2011), this paper incorporates the banking sector into a DSGE model to analyze the impact of declining housing prices on land financing, while also considering the dual negative effects of banking financial frictions on credit supply. The findings differ from the transmission mechanisms studied during periods of rising housing prices and offer theoretical and practical significance for understanding the impact of declining housing prices on the overall credit scale and macroeconomic fluctuations. Third, there is a relative lack of literature within a general equilibrium framework that examines the effects of reducing the RRR and lowering interest rates on existing housing loans. Given the close ties among China's real estate market, commercial banks, and land financing, this paper introduces three policy tools: reducing the RRR, lowering interest rates on existing housing loans, and injecting capital into commercial banks. It analyzes the transmission pathways and effects of these policy tools on housing price regulation.

As China pursues high-quality economic development driven by innovation, the financing constraints faced by asset-light innovation-oriented enterprises have become increasingly prominent. International experience highlights the emergence of “cash flow-based financing models,” where corporate's operating profits serve as the foundation for debt, proving more effective in supporting enterprise innovation and economic structural transformation. While China's financial structure remains predominantly indirect-finance-oriented, domestic banks have recently shifted their mindset by promoting various innovative instruments such as intellectual property pledges, equity-debt hybrid financing, and operating revenue-linked loans. Consequently, the loan approval rates for technology-intensive enterprises have shown significant improvement. Nevertheless, whether this bank-dominated financing framework can effectively foster the growth of innovative enterprises constitutes a critical practical issue that demands thorough academic investigation.
The theoretical framework of this study centers on the role of information asymmetry and risk levels in determining financing models. We posit that both collateral and cash flow can mitigate information asymmetry and agency problems, thereby enhancing firms' financing accessibility. However, the relative importance of these two factors varies with firm-specific characteristics. Smaller, riskier, and less profitable firms typically face more severe information asymmetry and higher default risk, making them more reliant on collateral-based financing. Conversely, larger, lower-risk, and more profitable firms generally possess more stable cash flows and stronger operational sustainability, which may reduce their dependence on collateral and increase the sensitivity of financing decisions to cash flow. Furthermore, external judicial framworks and targeted policy support for high-tech firms can amplify the role of cash flow-based financing by either reducing information asymmetry or mitigating risk exposure.
Using micro-level data from A-share non-financial listed firms in China between 2007 and 2022 (33,799 firm-year observations), this paper proceeds in three stages. First, we construct a baseline model to examine the impact of collateral assets and cash flow on firm financing. Second, we investigate heterogeneity in financing models across firms from the internal aspects (size, risk, and profitability of firms) and external aspects (bankruptcy reorganization legal systems). Third, we focus specifically on innovative enterprises, identified through both market-based criteria (strategic emerging industries and future industries) and policy-based criteria (specialized, refined, innovative enterprises), and employ PSM-DID methods to analyze the impact of supportive policies on these firms' financing models.
Our empirical findings yield several important insights. First, Chinese listed companies' financing constraints exhibit diversified characteristics, with both collateral and cash flow significantly facilitating loan acquisition. Second, firms' reliance on collateral has somewhat weakened over time, while the impact of cash flow has significantly strengthened, particularly after the implementation of bankruptcy reorganization systems in 2018. Third, the financing model varies significantly across firms with different financial characteristics: smaller, higher-risk, and less profitable firms are more sensitive to collateral, while larger, lower-risk, and more profitable firms are more sensitive to cash flow. Fourth, innovative enterprises, particularly those in strategic emerging industries, predominantly rely on cash flow rather than collateral for financing, which aligns with their generally favorable financial conditions. Fifth, legal system improvements and policy support have significantly enhanced the role of cash flow in corporate financing. Specifically, both credit support policies for strategic emerging industries and certification policies for specialized, refined, innovative enterprises significantly strengthen the sensitivity of financing to cash flow, reducing dependence on collateral.
Based on these findings, we propose several policy recommendations: (1) Improve the institutional infrastructure and risk control mechanisms for cash flow-based financing, including enhancing bankruptcy reorganization systems, promoting digital financial technologies, and improving accounting standards and information disclosure systems; (2) Expand the categories of acceptable collateral types and develop digital valuation systems for intangible assets; (3) Innovate financial service models, such as investment-loan linkage mechanisms and specialized banking services for innovative enterprises; (4) Establish differentiated policy support systems for innovative enterprises at different development stages; and (5) Strengthen the social credit system to reduce moral hazard in cash flow-based financing.
Our study contributes to the literature in several ways. First, it provides systematic empirical evidence on the diversity and evolution of corporate financing models in China, addressing the overemphasis on collateral dependence in existing research. Second, it offers micro-level evidence on how indirect financing supports innovative enterprises from both internal firm characteristics and external environmental perspectives. Third, it empirically verifies the role of institutions and policies in promoting the development of cash flow-based financing models, providing theoretical basis and policy references for improving innovative enterprise certification standards and related infrastructure.
Future research could broaden this work by incorporating more unlisted innovative enterprises in the sample, developing more refined measures of innovation capability, examining the combined effects of direct and indirect financing, and further exploring the role of digital finance and financial technology in alleviating financing constraints for innovative enterprises.

Promoting green and low-carbon development is pivotal to achieving high-quality growth. However, green products, characterized by quasi-public good attributes, often generate investment returns below investors' expected thresholds. Reducing financing costs is therefore crucial to enhancing returns and channeling social capital into green industries. Green credit, as a vital tool and policy instrument for supporting green transformation of the economy, plays a critical role in offering preferential loan rates to green enterprises. Enhancing commercial banks' lending support for green enterprises relies not only on the impetus of green finance policies but, more critically, on the credit market's recognition of green firms, while it has received insufficient attention in the existing literature. Against the backdrop of escalating environmental regulations intensity by the Chinese government and intensifying competition in green credit among banks, do green enterprises enjoy lower loan interest rates compared to their non-green counterparts？ What role do market forces play？ Moreover, how does their influence differ from that of policy factors？
This paper examines whether green enterprises enjoy lower loan rates compared to non-green enterprises,and particular focus on the roles of environmental regulation and market competition in shaping credit terms. Furthermore, it disentangles the distinct effects of policy interventions versus market forces on banks' green lending strategies. Building on China's unique green credit market characteristics, the paper then examines heterogeneous pricing patterns across different bank types and firm sizes. Finally, the study evaluates the pricing efficiency of green loans.
Using desensitized loan-by-loan data from a province in China, covering all corporate loans issued by banks from October 2020 to December 2022. We find that green enterprises receive significantly lower loan rates than their non-green counterparts, driven primarily by stricter environmental regulations and heightened green credit competition, which enhances the creditworthiness of green enterprises and compresses banks' marginal profitability respectively. This rate advantage reflects both market-based recognition of green attributes and policy-induced incentives. Significant disparities exist across banks and enterprises: state-owned banks offer the lowest rates to green firms, while small and medium-sized green enterprises (SMEs) receive more favorable rates but face stricter collateral requirements. Additionally, banks' green loan pricing effectively reflects credit risks, hence it is efficient.
Based on the research findings, the following policy recommendations are proposed: First, it is recommended to adopt differentiated policies to incentivize commercial banks to increase financial support for green enterprises, while fully leveraging the government's guiding and mandatory role in environmental regulation. Second, banks should integrate green credit policies with their customer base and asset structure to strengthen risk management capabilities in green lending process. Meanwhile, they should actively develop green financial products to provide diversified financing solutions for green enterprises of varying sizes. Third, authorities should not only clarify the basic requirements for disclosure, which include entities, content, format, and timelines, but also harness the power of the digital economy to improve green enterprises' disclosure capacity and motivation. Additionally, inter-departmental collaboration should be enhanced by establishing platforms for sharing environmental data and strengthening cooperation with financial institutions in data connectivity, thereby improving the efficiency of green finance capital allocation.
This paper contributes to the existing literature from the following three dimensions: Firstly, the paper enriches green credit research by exploring the roles of environmental regulations and market competition in banks' green loan pricing and further examining their differential impacts compared to policy factors. It provides theoretical insights into understanding banks' green lending behavior and policy formulation. Secondly, the research expands the study of commercial banks' green loan pricing behavior by utilizing representative loan-by-loan data to analyze differentiated pricing strategies for enterprises of varying sizes. It reveals banks' pricing practices through both interest rates and collateral requirements, offering valuable implications for improving resource allocation efficiency in green credit markets. Thirdly, the paper deepens research on the effectiveness of green development policies by comparing changes in green enterprise loan rates under the influence of fiscal policies, financial policies, and their combined effects. It provides empirical support for enhancing the design and implementation of green development policies.

This study investigates how digital transformation of financial infrastructure can alleviate long-standing financing constraints faced by micro, small, and medium enterprises (MSMEs) in China. As inclusive finance and digital finance are elevated to national priorities under China's financial reform agenda—highlighted in the Central Financial Work Conference and recent State Council guidelines—this research provides timely empirical insights into how digital innovation within financial institutions can enhance credit access for financially constrained firms. The focus of this research is on the People's Bank of China's Accounts Receivable Financing Service Platform (ARFSP), a centralized digital infrastructure that facilitates receivables-based collateral lending in supply chains.
Traditionally, MSMEs have struggled to access formal credit markets due to their lack of fixed assets, limited credit histories, and informational opacity. The ARFSP was initially launched in 2013 to address this issue by improving receivables transparency and enabling supplier firms to pledge accounts receivable to secure loans. While the early phase relied heavily on manual data upload and verification by core firms, the platform underwent a digital upgrade in 2016 that allowed for real-time system-to-system (S2S) integration with core enterprises' ERP systems. This innovation enabled automated, authenticated transmission of transaction data between firms and financial institutions, significantly reducing the cost and frictions of receivables verification, which in turn lowered the barrier to bank financing for suppliers.
Using detailed loan-level and firm-level data from the ARFSP between 2014 and 2022, the study empirically evaluates whether this digital infrastructure enhanced access to finance and improved loan terms for MSME suppliers. A difference-in-differences strategy exploits the staggered adoption of the S2S integration among core firms, comparing outcomes for suppliers associated with digitally connected firms to those still using the manual mode or not participating in the platform. To strengthen identification, the analysis further incorporates propensity score matching and triple-difference models. The findings show that digital connectivity significantly increases both the number of suppliers obtaining loans and the total loan volume extended through the platform. Importantly, the allocation of credit shifts toward smaller firms: account receivables of MSMEs rise in both frequency and value share. Moreover, the new loans enabled by digital connectivity are more inclusive in design—smaller in size, longer in duration, and lower in interest rates—thus directly aligning with the goals of inclusive finance.
These financial improvements are accompanied by tangible enhancements in business performance. Suppliers connected through digitally integrated core firms exhibit better liquidity management, lower debt service costs, and stronger sales and profitability. The benefits are not confined to suppliers alone: core firms also experience gains in revenue and financial resilience, likely reflecting improved operational efficiency and supply chain coordination. Such results provide rare micro-level evidence that digital financial infrastructure can produce win-win outcomes across supply chain tiers, particularly in ecosystems involving resource-constrained firms. This reinforces theoretical arguments that public infrastructure for information sharing can act as a collective good, reducing credit frictions and enhancing allocation efficiency in financial markets.
The mechanism analysis further reveals that, on the one hand, the S2S connection significantly reduces the cost of uploading and processing account receivables data—an efficiency advantage that becomes particularly prominent for core firms with extensive supplier networks. On the other hand, in regions where bank lending is more constrained, the financing facilitation brought by digitalization is especially pronounced, underscoring its potential to improve the geographic distribution of credit and promote more balanced regional development. These insights highlight how digital infrastructure not only addresses information frictions at the firm level, but also functions as a policy lever for achieving broader spatial equity in credit allocation.
The study contributes to multiple academic literatures. Within supply chain finance, it highlights the role of institutional infrastructure—beyond inter-firm contracting—in shaping financing dynamics. In the financial intermediation and development literature, it empirically validates how information systems can reduce credit risk, extend lending horizons, and promote inclusive finance. Furthermore, by leveraging detailed administrative data and advanced causal inference techniques, the research sets a methodological benchmark for evaluating policy innovations in financial markets. Notably, the findings suggest that digital transformation of financial infrastructure should be treated as a core component of inclusive finance strategy, rather than a supplementary tool.
Policy implications from this research are clear and actionable. Authorities should accelerate the adoption and integration of digital platforms like the ARFSP, especially among large core firms with extensive MSME supplier networks. Financial regulators may consider offering technical or fiscal incentives to encourage ERP integration with national platforms. Equally important is the need to promote a narrative of mutual benefit around data sharing, as many core firms remain hesitant to expose transaction-level data. The study shows that such sharing not only benefits MSMEs but also improves the financial performance of the core firms themselves, creating a virtuous cycle that strengthens supply chain resilience.
This research opens avenues for comparative studies across different country contexts, especially in emerging markets where digital financial infrastructure remains underdeveloped. Future work could also examine the broader spillover effects of such platforms, including labor market responses and innovation incentives. Additionally, as digital ecosystems evolve, it will be important to understand how firms dynamically adapt their financing behavior, investment strategies, and risk management practices in response to enhanced financial infrastructure. Overall, this study affirms the transformative potential of digital public goods in the financial sector, and underscores their central role in building an inclusive, efficient, and resilient economic system.

The high-cost negative consequences of environmental pollution, including increased infant mortality and neurodevelopmental disorders, reduced educational attainment, and labor market participation, have garnered widespread global attention. Green development has increasingly become a global consensus, with governments actively formulating corresponding environmental regulatory policies to enhance pollution control capabilities and mitigate the adverse effects of environmental pollution. China has long implemented a pollution discharge fee system to control corporate pollution emissions. However, due to apparent deficiencies such as low fee standards, insufficient pollutant coverage, and weak enforcement, the legislative authority deliberated and passed the Environmental Protection Tax Law on December 25, 2016, which came into effect on January 1, 2018. Its implementation marked a transition toward the legalization of China's environmental governance, where taxpayers refusing to pay environmental protection taxes will face legal sanctions rather than merely administrative penalties. Green transformation is not only a critical component of China's industrial system upgrading but also a fundamental characteristic of its modern industrial system. The dynamics of firm entry and exit are not only important sources of economic growth and job creation but also crucial intermediate links in the formation of industrial systems. Understanding how environmental regulations influence the green transformation of the industrial systems by affecting the entry dynamics of firms in both heavy-pollution and clean industries is of great significance for building a modern industrial system, promoting high-quality economic development, and achieving Chinese-style modernization
Theoretically, the increase in entry costs will restrict entrepreneurs with low initial wealth and external financing constraints from entering the market. When entrepreneurs have sufficient wealth and external financing capacity, the entry decisions also depend on the comparison between the present value of expected returns and entry costs. The implementation of the Environmental Protection Tax Law has significantly improved green innovation and environmental performance among incumbent firms in heavy-pollution industries. Higher levels of green innovation and patent holdings help polluting firms maintain leading positions and market share, which to some extent raises the technological barriers and entry thresholds for new firms, thereby leading to an increase in entry costs. At the same time, the implementation of the Environmental Protection Tax Law has increased the tax fees that enterprises must pay for pollution emissions, raising the production and operational costs of polluting firms and reducing their future profit margins. It can thus be expected that the increase in entry costs and production costs brought about by the implementation of the Environmental Protection Tax Law will discourage the entry of firms into heavy-pollution industries. A direct manifestation of the reduction in firm entry into these industries is the decline in the share of heavy-pollution industries, which will direct more social and financial resources toward clean industries, ultimately achieving a greener transformation of the industrial structure
To validate the above expectations, we use full-sample industrial and commercial enterprise registration data to examine the effect of the Environmental Protection Tax Law implementation on firms' entry decisions. Results from difference-in-difference-in-differences (DDD) tests show that after the implementation of the law, the number of new entrants in heavy-pollution industries decreased by approximately 14% in regions where the pollutant tax standards for taxable pollutants were raised. Further tests show that the inhibitory effect of the Environmental Protection Tax Law on firm entry primarily exists in non-state-owned enterprises, industries with higher entry barriers, and regions with stricter tax enforcement. Finally, we examine the macro effects of the Environmental Protection Tax Law implementation on regional industrial structure, environmental quality, and economy performance. The results show that by inhibiting firm entry into heavy-pollution industries, the implementation of the law has significantly reduced the gross industrial output and employment in these sectors, thereby promoting the green transformation of industrial structures in regions with raised tax standards. At the same time, we find that the implementation of the law has significantly reduced regional industrial pollution emissions, but has not had any significant negative impact on local economic output and employment.
This paper makes contributions to the following three aspects: First, it contributes to research on the economic effects of environmental protection taxes. We investigate how the Environmental Protection Tax Law affects firm entry, industry dynamics, and thus industrial structures, providing insights and reference value for comprehensively understanding and evaluating the law's economic effects. Second, it contributes to research on determining factors of entrepreneurial activity. The Environmental Protection Tax Law represents China's first legislative attempt to curb environmental pollution, aiming to strengthen environmental regulation through the rigidity of taxation law enforcement. Unlike regional and short-term regulations, taxing pollution emissions accompanies the entire production and operation process of enterprises, affecting not only firms' entry costs but also their subsequent production costs, future profits, and thus becoming one of the critical factors influencing firm entry behavior. Third, as environmental protection taxes constitute real costs for microeconomic entities, exploring whether and to what extent the Environmental Protection Tax Law can achieve a “double dividend” holds practical significance. We find that the law's implementation significantly reduces regional pollution emissions without significantly decreasing economic output or employment, indicating that China's current environmental protection tax system design have achieved a “weak double dividend” to some extent. Additionally, the study reveals that the law promotes the green transformation of regional industrial structures, which is of great significance for building a modern industrial system and, further a modern economic system.

The governance risks associated with Village Banks pose significant challenges to the stable operation of China's financial markets. As key financial institutions serving agricultural, rural, and farmer-related sectors in county-level regions, Village Banks have played an active role in strengthening rural financial systems and promoting rural economic development. However, in recent years, some Village Banks have deteriorated into high-risk institutions with extreme financial risk events—such as the withdrawal crises at Village Banks in Henan Province—not only severely harmed depositors' interests and hindered the sustainable development of these banks, but also raised concerns over potential systemic financial risks. Therefore, uncovering the root causes of governance failures and resolving the governance dilemmas specific to Village Banks are crucial steps in enhancing the financial system's capacity to support rural development and ensuring long-term financial stability.
This paper focuses on the naturally formed pyramidal ownership structures within Village Banks and selects the public listing of their controlling Sponsoring Banks as an exogenous shock to study the effect of transparency on governance outcomes. Using a sample of Village Banks from 2013 to 2023, we adopt a multi-period difference-in-differences (DID) approach to empirically examine the impact of increased information transparency on the governance and performance of Village Banks. The results show that the listing of Sponsoring Banks significantly increases both the probability and quality of information disclosure by Village Banks. Enhanced transparency improves internal governance structures—the vibrancy of the board of directors and the degree of managerial discipline both improved, while the proportion of pledged equity declines. At the same time, external oversight mechanisms are reinforced, as evidenced by a significant rise in regulatory penalties and media coverage. Consequently, the overall performance of Village Banks improves, with return on assets (ROA) rises by 0.58 percentage points while the non-performing loan ratio (NPL) drops by 2.26 percentage points.
Furthermore, this study documents that certain opaque governance arrangements—such as overly complex pyramid structures, the delegation of board chairpersons by provincial rural credit cooperatives, and the misalignment of regulatory responsibilities of Sponsoring Banks—undermine the positive effect of Sponsoring Bank listings on transparency. These findings suggest that such distortions weaken the transmission of good governance practices and performance improvements. The evidence thus highlights that enhancing transparency is key to resolving governance bottlenecks in Village Banks. Moreover, it demonstrates the existence of corporate governance transmission effects within pyramidal ownership chains: positive governance mechanisms introduced through listing—such as improved transparency and stronger accountability—can be transmitted downstream to Village Banks; conversely, flaws in upper-tier governance can also cascade through the ownership hierarchy, potentially reaching its lowest tier.
Based on these findings, the paper offers the following policy implications. First, in line with the regulatory agenda of the National Administration of Financial Regulation, standards for Village Bank information disclosure should be further refined to ensure accuracy, timeliness, and completeness. Second, the qualification and screening criteria for Sponsoring Banks must be tightened to reinforce their leadership role, thereby promoting effective transmission of sound governance practices to Village Banks. Third, institutional arrangements must ensure alignment between responsibilities and authority, clarifying the defined roles for central regulators, local financial bureaus, provincial rural credit union federations, and ultimate controllers to prevent the emergence of unbalanced or ambiguous governance structures. It is also essential to curb the growing complexity of pyramidal ownership structures, which exacerbates managerial difficulty and risk accumulation through multi-layered governance chains.
This study contributes to the literature in three main ways. First, it addresses the longstanding corporate governance blind spot of Village Banks, highlighting the crucial role of transparency in overcoming governance challenges, and thereby enriching the banking governance literature within the banking sector. Second, using the context of Village Banks, the study provides empirical evidence on the dynamic effects of upper-tier parent company governance features on lower-tier subsidiaries within a pyramid ownership structure. It innovatively conceptualizes frames and empirically verifies governance transmission effects and sheds light on the “black box” of governance in pyramid structures. Third, by taking Village Banks as a case study, the paper reveals the positive spillover effects of parent corporate listing on the transparency and governance of controlled subsidiaries. It provides practical evidence supporting listing as a policy tool to promote transparency and governance standardization. From a policy perspective, this research offers actionable insights for improving Village Bank governance—particularly through enhancing transparency—and proposes a potential solution to one of the long-standing issues in China's financial system. Future research may expand this framework to explore horizontal transmission mechanisms, governance convergence, and broader system-level dynamics within Village Bank systems, thereby advancing theories in corporate and rural financial governance.

Against the backdrop of the current rapid development of the capital market, the quality of information disclosure is particularly critical to the quality development of companies. As a supplement to mandatory information disclosure, the interactive platforms of stock exchanges have become an important innovation in improving investor relations management through a two-way communication mechanism. On the interactive platform, instant Q&A between investors and companies can reflect not only the companies' response strategy to market dynamics, but also the level of voluntary disclosure by companies, which has become an important dimension in assessing the quality of information disclosure. Credit rating agencies (CRAs), as important information intermediaries in the capital market, rely on diversified information for their risk assessment. Therefore, the timeliness and unstructured feature of Q&A information on interactive platforms can be an effective reference for rating agencies. The rating system requires CRAs to combine quantitative information with qualitative analysis in an organic way, which further elevates the importance of non-standardized textual information in rating decisions. However, existing research focuses on the impact of financial indicators on rating outcomes, and the value of textual information disclosed via interactive platforms is still underexplored. Theoretically, the Q&A information of interactive platforms may significantly affect the level of corporate credit ratings through rating adjustment factors, but this path has not yet been empirically tested. Therefore, the purpose of this paper is to explore in depth the effect of interactive disclosure on corporate credit ratings and provide decision support for stakeholders.
To address the above issues, we select a research sample of Chinese A-share listed companies in Shanghai and Shenzhen from 2013 to 2023. We find, first, that the negative tone of interactive disclosure texts and strategic managerial responses significantly lowers the level of issuer credit ratings, and this effect is more pronounced for rating agencies with higher reputations and foreign backgrounds. Second, the negative tone of interactive disclosure texts lowers issuer credit ratings by intensifying corporate financing constraints and increasing debt agency costs, and the strategic response lowers issuer credit ratings by increasing information asymmetry and decreasing stock liquidity. Third, the downgrade in issuer credit ratings caused by the negative tone of interactive disclosure texts and strategic responses may further reduce the amount of trade credit financing available to firms and increase the cost of bond issuance.
The marginal contributions of this paper are mainly as follows: First, it enriches the research boundaries related to the economic consequences of interactive disclosure. Contrary to existing studies, the complex relationship between interactive disclosure and issuer credit ratings is explored in depth from the perspective of the textual features of interactive disclosure, further expanding the research boundaries on the economic consequences of interactive disclosure. Second, it enriches research on the factors influencing credit ratings. By using natural language processing (NLP) technology to construct textual indicators, the effective value of textual information of interactive disclosure on credit ratings is systematically presented. Third, from the perspective of debt financing, the economic impact of interactive disclosure on trade credit financing and bond issuance costs is examined through the financing intermediary role of credit ratings, further enriching research in this area. Fourth, by analyzing the mechanisms, heterogeneity and economic consequences of the textual features of interactive disclosure on issuer credit ratings, we not only deepen the theoretical understanding of the qualitative features of interactive disclosure and the determinants of credit ratings, but also provide useful policy insights for improving the construction of interactive platforms on stock exchanges to support better rating decisions by CRAs.
The policy implications of this paper are as follows: from the corporate level, firms should establish a complete interactive information processing management system. First, companies can implement a categorical response mechanism, use NLP technology to identify high-frequency questions, and require the secretary of the board of directors to conduct a second-level verification and source annotation for important responses. Second, companies can develop an impact analysis system for information disclosure, and anticipate the impact of responses on issuer credit ratings and debt financing so as to avoid avoiding the truth. At the rating agency level, CARs should use sentiment analysis models to quantify the proportion of negative tone and capture changes in management attitudes. They can use semantic association mapping techniques to identify response strategies and incorporate the analysis into credit rating models. At the investor level, investors should explore the textual features of interactive information from multiple perspectives, quantify the proportion of both negative tone and the degree of strategic intent, and comprehensively assess the development prospects of companies. At the regulatory level, regulators should optimize the operating mechanism of the exchanges' interactive platform. First, regulators can establish a categorized review and quality assessment system that requires substantive responses and reduces ambiguity, with regular quality spot checks by the exchange. Second, regulators can jointly develop automated monitoring tools to capture and assess risk signals in real time and incorporate them into credit file management.

Before 2009, due to restrictions from the Budget Law of the People's Republic of China and other regulations, local governments were not permitted to raise funds directly. Instead, they had to rely on local government financing vehicles (LGFVs) or state-owned enterprises as financing agents, often pledging land assets or future fiscal revenues as collateral to obtain loans from banks or issue urban investment bonds (chengtou bonds). Starting from 2009, China resumed the issuance of local government bonds, piloting models of the “agency-issuance and agency-repayment” and “self-issuance and agency-repayment”. However, development competition among local governments and implicit guarantees gave rise to soft budget constraints, leading to continuous growth in local government debt, especially hidden debt, thereby escalating potential debt risks. In response to the continuous increase in local government debt and its negative effects, China began to comprehensively implement reforms in the management system of local government debt in 2015. Following the approach of “opening the front door and blocking the back door”, a policy of “self-issuance and self-repayment” (SISR hereafter) for local governments was promoted. By allowing local governments to issue government bonds within approved limits, the growth of hidden local debt was curbed, and the structure of local debt was optimized. Under the SISR, local governments are required to enhance the management and quality of bond information disclosure, and reinforce market constraints and social supervision. Meanwhile, the issuance and trading of a large number of local government bonds have promoted the formation of a relatively large and active local government bond market.
This paper focuses on the incremental information brought about by the SISR reform, exploring whether such information spills over into the corporate credit bond market, particularly influencing the effectiveness of credit ratings, aiming to reveal the economic consequences of local government bond reform from a novel perspective. The reform has led to increased transparency regarding local governments' fiscal health, policy orientation, and economic fundamentals. In addition, the prices in the active local government bond market more accurately reflect the credit risk of local governments and their debts. Given the close relationship between firms' development and local government conditions, this information provides valuable input for investors and other market participants in assessing the credit risk of corporate bonds issued in that region. On the one hand, credit rating agencies (CRAs) can leverage local bond information to improve their assessment accuracy; on the other hand, the availability of such information increases market and regulatory scrutiny over potential rating biases, intensifying reputational and compliance pressure on CRAs, and driving them to improve the quality and effectiveness of their ratings. Therefore, this paper takes credit bonds as the research object, uses the policy shock of the SISR reform of local government bonds carried out by various local governments in China, and examines its impact on the effectiveness of credit bond ratings. The findings reveal that the SISR reform improves the effectiveness of credit bond ratings. The tests of the mechanism show that this effect is more pronounced in bonds issued by local state-owned enterprises and LGFVs, as well as in regions with higher trading volumes of local government bonds, verifying the existence of an information spillover effect; In addition, the primary channel through which the reform improves rating effectiveness is by enhancing rating quality. Heterogeneity tests show that the positive relationship between SISR reform and the effectiveness of credit ratings mainly exists when the financial transparency of local governments is relatively low. Lastly, the study finds that credit ratings of local government bonds themselves can generate spillover effects onto corporate credit ratings.
The theoretical and policy contributions of this paper are as follows. First, it enriches the literature on the economic consequences of local government debt governance by approaching it from the perspective of corporate credit ratings. Second, it offers rare empirical evidence based on China's bond market, using a policy reform as an exogenous shock to identify the spillover effects of local bond information disclosure on the credit bond market. Third, the findings provide valuable policy insights from the perspective of market information, contributing to the enhancement of market discipline, cross-market regulatory coordination, and the improvement of credit rating quality and effectiveness in China's bond market.

The Chinese government has consistently played a proactive role in economic development. Over the past two decades, local governments have promoted substantial infrastructure investments, primarily through land-based finance and off-balance-sheet debt instruments. Notably, the “4-trillion yuan” stimulus package launched in 2009 aimed to boost economic growth through counter-cyclical measures. While these policies significantly enhanced short-term economic performance, they also led to the accumulation of local government debt burden. As the Chinese economy entered a period of deep structural adjustment, traditional growth drivers gradually weakened, and risks associated with local government debt became increasingly prominent, making implicit local government debt a critical issue in policy regulation.
In recent years, China has further intensified and refined its fiscal policy tools. In October 2023, the government issued an additional one trillion yuan in sovereign bonds and raised the fiscal deficit ratio. Throughout 2024, multiple rounds of additional bond issuances and debt restructuring policies have been introduced, aiming to stimulate economic recovery through expanded fiscal expenditure. However, whether the rapid increase in government debt can effectively drive economic growth, and to what extent it can do so, remains an open question. Addressing these issues fundamentally requires a scientific estimation of the fiscal expenditure multiplier. The higher the fiscal multiplier, the more significant the impact of expansionary fiscal policy, and the greater the potential to ease pressures on the economic recovery.
Against this backdrop, China began implementing a local government implicit debt swap program in 2015. The core objective of this policy is to alleviate local governments' debt burdens and improve the efficiency of fund utilization by replacing inefficient and high-cost implicit debt with more transparent financing mechanisms. However, the actual economic effects of this policy have not been fully assessed. Existing studies show significant divergence in fiscal multiplier estimates and generally lack effective control for policy endogeneity. To fill this gap, this paper focuses on the following core research questions: Has the local government debt swap significantly promoted local economic growth？ How should the fiscal expenditure multiplier be accurately estimated, and does its magnitude exhibit heterogeneity under different economic conditions？ What are the underlying mechanisms through which local fiscal expenditure influences growth？ Does the implicit debt swap generate spillover effects that impact coordinated regional development？
This study combines theoretical analysis with empirical investigation. On the theoretical side, it first provides a comprehensive review of classical studies on fiscal multipliers. It then links the local government implicit debt swap policy with local fiscal expenditure, exploring its potential impacts on fiscal spending and economic growth from the perspectives of debt structure optimization and improved fund utilization efficiency. On the empirical side, leveraging the exogenous nature of the debt swap policy, this paper utilizes a panel dataset at the prefectural level and employs a difference-in-differences (DID) model to identify the policy effects, supplemented by instrumental variable (IV) methods to estimate the fiscal expenditure multiplier more precisely. To ensure the robustness of the results, multiple heterogeneity tests and robustness checks are conducted, including subgroup analyses based on economic cycles, household leverage levels, and initial regional capital stocks.
The main data sources include the CEIC database, the Wind database, and annual City Statistical Yearbooks, covering the period from 2010 to 2021. This study first quantifies the implementation scope and intensity of the implicit debt swap policy and then estimates its direct effects on local fiscal expenditure and economic growth. The results show that the implicit debt swap policy significantly increased local fiscal expenditure, thereby stimulating rapid regional economic growth. Specifically, after the debt swap, fiscal expenditure in the treatment group increased by 20.62% relative to the control group, while regional total output rose by 40.64%. Fiscal multiplier estimation results indicate that a 1% increase in local fiscal expenditure leads to a 2.071% increase in cumulative regional output, corresponding to a fiscal multiplier significantly greater than 1. This finding suggests that local fiscal expenditure in China yields extremely high marginal returns.
Further heterogeneity analyses reveal several important conclusions. First, the fiscal multiplier is significantly influenced by the state of the economic cycle. When the economic growth rate falls below the potential growth rate, the fiscal multiplier increases markedly. This result is consistent with the theory of counter-cyclical macroeconomic policy: when effective demand is insufficient, expansionary fiscal policy has a stronger stimulative effect on economic growth. Second, high household leverage significantly weakens the effectiveness of fiscal policy, reducing the fiscal multiplier. This finding aligns with the balance sheet recession hypothesis, which posits that when private sector debt levels are excessively high, households tend to prioritize debt repayment over consumption or investment, thereby weakening the economic impact of fiscal expenditure. Third, the initial regional capital stock levels do not show a significant effect on the fiscal multiplier. This suggests that China's high fiscal multiplier primarily stems from direct demand-side effects rather than long-term supply-side factors such as capital accumulation or productivity improvements. This finding further underscores the crucial role of short-term demand management through fiscal policy in China's macroeconomy.
Based on the above analysis, this paper offers several policy recommendations. First, a more proactive fiscal stance should be adopted. The large fiscal multiplier estimated in this study indicates that the Chinese economy has been operating below its potential output for an extended period, implying a persistent effective demand gap. Under such conditions, fiscal authorities should actively fill the demand shortfall through more expansionary fiscal policies, including breaking through the conventional 3% deficit-to-GDP ceiling and adopting stronger counter-cyclical measures. Second, local governments should continue to alleviate their implicit debt burdens through debt swaps. For local governments with heavy hidden debt burdens, debt swaps effectively expand fiscal space and promote higher output. Hidden debts not only increase financing costs but also elevate financial risks. In the coming years, the government should continue to vigorously implement debt swaps under strict controls on new implicit debt, aiming to eliminate existing implicit debts through refinancing bonds and other instruments. Third, greater fiscal efforts should be initiated at the central government level. Local government debt lacks macroeconomic stabilization functions and must eventually be repaid from future revenues, limiting its counter-cyclical effectiveness. By contrast, debt issued by a sovereign central government denominated in its own currency does not necessarily require future repayment and can sustain long-term macroeconomic management. Thus, future counter-cyclical fiscal policy should rely more on central government leverage to maintain low government borrowing costs and expand fiscal capacity. Lastly, structural deleveraging efforts should be sustained to maintain the overall macro leverage ratio while selectively reducing debt levels in vulnerable sectors. This paper's heterogeneity analysis finds that excessively high private debt levels diminish the effectiveness of fiscal policy. Proactively reducing private sector debt burdens under policy guidance is crucial to avoiding a balance sheet recession and enhancing fiscal policy efficiency.
This paper contributes to the literature in four major ways. First, by selecting appropriate instrumental variables, it estimates a relatively large local fiscal expenditure multiplier. We argue that the chosen instrument exhibits greater exogeneity, leading to more accurate estimates. Second, it explores the transmission mechanisms behind the fiscal multiplier, suggesting that the large multiplier effect primarily arises from demand-side channels—specifically, government spending increases private sector incomes, thereby generating multiplier effects. Third, the paper successfully identifies the causal effects of the 2015 implicit debt swap policy on local fiscal expenditure and regional output. Given the enactment of the new Budget Law and the scale of the debt swaps totaling several trillion yuan, empirically evaluating this major fiscal initiative is of great importance. Lastly, on the policy front, the paper provides robust empirical support for China's current macroeconomic regulation strategies and debt restructuring initiatives.