Since the second quarter of 2022, the year-on-year growth of new residential property prices across China’s 70 large and medium-sized cities has remained negative. Concurrently, the macroeconomy has been characterized by stable yet slightly declining leverage ratios in the household sector, weak real estate development investments, and credit contractions. Existing theoretical studies mostly characterize housing price fluctuations based on the collateral constraint mechanism that captures the positive feedback loop between housing prices and debt. Nevertheless, from the perspective of household balance sheets, changes in debt exert a limited impact on households’ intertemporal decision-making. Hence, this mechanism is insufficient to explain the recent economic characteristics of China. To address this gap, this paper proposes a household balance sheet constraint mechanism that captures the positive relationship between housing prices and household net worth. By constructing a dynamic stochastic general equilibrium (DSGE) model embedded with this mechanism, this paper successfully replicates the key features of China’s recent macroeconomic data.
This paper arrives at three key findings through empirical and theoretical analysis. First, a loss of housing net worth triggers the household balance sheet constraint mechanism, which exerts negative static and dynamic multiplier effects on housing prices and household net worth. This mechanism drives a decline in housing prices and a contraction of household sector balance sheets, and then spills over to other sectors via the inter-sectoral balance sheet channel, leading to a credit contraction and downturn in the real economy. In particular, the completed real estate development investment remains in a state of prolonged weakness. Second, the narrower the space for household sector leverage expansion, the stronger the household balance sheet constraint mechanism, and the larger the magnitude of macroeconomic fluctuations induced by shocks to household housing net worth. Third, countercyclical adjustments to the interest rates on outstanding mortgage loans targeted at housing price fluctuations reduce household debt-servicing costs, which in turn improves household net worth, thereby weakening the household balance sheet constraint mechanism. Consequently, this policy is able to mitigate the macroeconomic fluctuations caused by housing net worth shocks.
Taken together, these conclusions carry important policy implications: the key to mitigating housing net worth shocks lies in weakening the intensity of the household balance sheet constraint mechanism that captures the positive feedback loop between housing prices and household net worth. In practice, lowering interest rates on outstanding mortgage loans bolsters household net worth, which in turn weakens the negative feedback loop between falling housing prices and household net worth erosion, thus effectively cushioning macroeconomic fluctuations induced by housing net worth shocks. Building on this, governments may consider three approaches to further improve household net worth: cutting household expenditures, expanding household income, and stabilizing housing prices.
The marginal contributions of this paper are embodied in three specific aspects. First, this paper proposes the household balance sheet constraint mechanism and verifies its amplification and transmission effects on household housing net worth shocks by constructing a DSGE model. It provides a concrete and testable DSGE framework for existing theories that emphasize the household balance sheet transmission channel during housing price downturns, thereby enriching the theoretical literature on the macroeconomic implications of household balance sheets. Second, the model constructed in this paper captures the recent economic phenomena in China characterized by declining housing prices, household sector balance sheet contraction, weak real estate development investment, and simultaneous credit tightening. It offers theoretical insights for understanding the persistent downturn of China’s recent real estate market and provides a theoretical framework for relevant policy simulations. Third, this paper simulates the effectiveness of housing regulatory policies in addressing household housing net worth shocks, which provides theoretical support for the formulation and improvement of China’s housing regulatory policies and also offers policy implications for further stabilizing the real estate market.

The Fourth Plenary Session of the 20th Central Committee of the Communist Party of China emphasized the imperative to “accelerate the green transition in all areas of economic and social development in an effort to build a beautiful China”. This transition, however, typically entails substantial, long-term financial commitments. In the face of heightened global financial pressures and the declining profitability of banks, credit resources are currently shifting from green to non-green sectors, increasing the pressure of “de-greening”. Against this backdrop, optimizing credit allocation and guiding financial resources to support the green economy have become critical challenges for China’s economic and financial strategy. To address this, this paper is the first to propose a novel index of “De-greening of Credit Allocation (DGCA)”, which provides a quantitative measure of the extent to which credit resources shift from green to brown firms within Chinese provinces, and further investigates the relationship among systemic financial stress, credit de-greening, and credit risk.
In China’s bank-dominated financial system,credit allocation plays a pivotal role in facilitating the transition toward a green economy. However, as global systemic financial pressures intensify, empirical research fails to provide clear and systematic conclusions regarding whether credit resources shift away from green sectors and whether such shifts generate latent financial risks. Although a growing number of studies have examined resource reallocation under financial stress scenarios, most of them focus on capital markets such as equities and bonds, while paying limited attention to credit allocation. Moreover, prior research lacks both a clear consensus on the direction of financial resource reallocation and a systematic evaluation of the risks it entails. To this end, this paper establishes an analytical framework of “systemic financial stress - credit de-greening - credit risk,” which sheds light on the internal logic of credit reallocation in periods of financial stress and further explores the financial vulnerabilities arising from credit de-greening. These findings offer important implications for enhancing credit support for the green transition and safeguarding financial stability during the transition process.
Specifically, this paper constructs a provincial-level DGCA index based on a sample consisting of 4,652 Chinese listed firms from 2010Q1 to 2023Q1. The value of the DGCA index appears to be higher in several western provinces, implying tighter credit de-greening constraints on the local firms that may hinder the low-carbon transition. Empirical analysis reveals that systemic financial stress has a significantly positive effect on the DGCA index. Banks’ “short-termism” serves as the primary channel: as financial pressure intensifies, banks shift their focus from long-term sustainability to short-term economic returns, discount the long-run benefits of green firms, and interpret the declines in green firms’ stock returns as signals of short-term deterioration, thereby tightening green credit and inducing credit de-greening. Heterogeneity analysis indicates that the effect of financial stress on credit de-greening is more pronounced during economic downturns and periods of high policy uncertainty. We also decompose financial stress series into positive and negative variations and find that credit de-greening significantly worsens as financial pressure rises but is difficult to reverse when financial pressure decreases.
Further analysis reveals that an increase in the credit de-greening index significantly amplifies credit risk. In particular, the DGCA index exerts a significantly positive effect on the credit risk of green firms, while this effect is negative but statistically insignificant for brown firms. These results indicate that credit de-greening primarily drives overall credit risk by increasing the default likelihood of green firms. Spatial Durbin model estimates reveal significant direct, indirect, and total effects of the DGCA index on most credit risk indicators, suggesting that credit de-greening in a given province not only significantly increases local default probabilities, but also generates positive spatial spillovers to neighboring provinces, thereby exacerbating regional credit risk.
Based on these findings, the paper offers three key policy recommendations. First, greater attention should be paid to the issue of credit de-greening in western regions, with enhanced targeted credit support for green industries in key areas. Second, counter-cyclical policy efforts should be strengthened to mitigate the driving effect of systemic financial stress on credit de-greening. Third, inter-provincial coordination in financial regulation should be enhanced to prevent the cross-regional transmission of risks arising from localized credit de-greening.

In recent years, China's local government debt has continued to expand, leading to an accumulation of associated risks. The mainstream approach historically employed by local governments to address risk shocks and achieve debt sustainability has been fund relocation. While this method possesses strong short-term “blood transfusion” capabilities, it carries potential risks in the long run. Industrial upgrading serves as an effective “hematopoiesis” mechanism, compensating for the limitations of fund relocation. At this stage, achieving local debt sustainability does not solely entail controlling the scale of local debt; rather, it emphasizes striking a balance between short-term “blood transfusion” through fund relocation and long-term “hematopoiesis” via industrial upgrading. This balanced approach aims to promote local economic development while safeguarding against systemic financial risks.
Due to the presence of implicit guarantees, substantive defaults are rare in China's local government debt market. However, a segment within this debt structure—non-standard debt contracts (commonly referred to as “non-standard” debt)—has seen its scale expand and experienced numerous defaults. These non-standard debt defaults expose underlying local debt risks, constrain sustainable local debt management, and incur significant economic consequences. Consequently, this paper addresses the following key questions: Are short-term fund relocation and long-term industrial upgrading effective pathways for local governments to respond to non-standard defaults? Under what conditions are local governments more inclined to adopt fund relocation strategies? Conversely, under what circumstances do they prioritize long-term industrial upgrading strategies to prevent debt risks?
Based on the above analysis, this paper adopts the following research framework: Following non-standarddebt defaults, the dual pathways of short-term fund relocation and long-term industrial upgrading can provide local governments with liquidity and developmental momentum, thereby mitigating financial risks and achieving debt sustainability. Through manual retrieval and screening of publicly available information, this study compiles data on over one hundred instances of non-standard defaults involving local government financing vehicles (LGFVs) between 2014 and 2021. By matching this with macroeconomic datasets, it examines the impact of non-standard defaults on debt sustainability. Grounded in theoretical analysis and practical experience, the study categorizes pathways to local debt sustainability into fund relocation and industrial upgrading, formulating corresponding hypotheses. It then tests the effectiveness of these different pathways and further investigates their applicable conditions and the circumstances prompting a shift from one strategy to the other.
The findings reveal that non-standard debt defaults undermine local debt sustainability by transmitting risk signals. Local governments can mitigate this adverse impact through short-term “blood transfusion” achieved via fund relocation methods such as upper-level government support, as well as through long-term “hematopoiesis” facilitated by industrial upgrading. Further analysis indicates that reliance on “blood transfusion” through fund relocation exposes local governments to two significant pressures: rising borrowing costs and “snowballing” debt. Consequently, some local governments transition towards promoting industrial upgrading to foster fiscal “hematopoiesis”, and thus shift toward “resolving debt through development” .
Using China's unique instances of actual non-standard defaults by LGFVs as a starting point, this paper conducts a systematic study of debt sustainability issues. By exploringthe impact mechanisms of short-term fund relocation (“blood transfusion”) and long-term industrial upgrading (“hematopoiesis”) on local debt sustainability, it enriches debt sustainability theory from a risk prevention perspective. The study provides insights into the applicable conditions for fund relocation and industrial upgrading, addressing the critical question of how to implement “resolving debt through development.” This research contributes to the theoretical underpinnings of local debt sustainability, offers theoretical support and optimization ideas for differentiated local debt management, and provides references for improving local government debt financing mechanisms and constructing new models for local debt management.

Local government debt risks and fiscal sustainability pressures have become increasingly salient in China, raising a central governance question: when a large share of liabilities is accumulated through local government financing vehicles (LGFVs) and remains partially off budget, how do local governments actually cope with repayment peaks under the constraints of the budget system? While existing studies have intensively examined why implicit debt expands, emphasizing soft budget constraints, fiscal incentives, and implicit guarantees, much less is known about how implicit debt is repaid in practice, especially when LGFV bonds approach maturity and refinancing conditions tighten. This paper fills this gap by identifying and explaining local fiscal responses to bond maturity pressure from the perspective of “Debt-to-Fee Substitution”.
In theory, LGFVs are corporate entities that should rely on their own assets and cash flows for debt repayment. In practice, however, investors often price LGFV bonds based on expectations of government support, and local governments have strong incentives to prevent disorderly defaults that could trigger regional credit contraction and financial instability. This institutional tension suggests that when bond maturities concentrate and refinancing gaps emerge, local governments may rely on fiscal mechanisms embedded in the budget process to buffer repayment pressure, even in the absence of explicit bailout obligations. We therefore ask whether LGFV bond maturity pressure induces systematic changes in local budget targets and execution, and how such fiscal responses are ultimately transmitted to firms.
To examine these issues, we assemble a prefecture-level panel dataset from 2008 to 2020 by manually collecting information on LGFV bonds and combining it with fiscal budget and final accounts data. Our key explanatory variable is net bond maturity pressure, defined asthe difference between the volume of maturing LGFV bonds and new issuance in a given city-year, which directly captures short-term liquidity stress faced by local governments. We further construct a measure of excessive budget growth targets, defined as the residual component of budgeted revenue growth after controlling for economic fundamentals and institutional determinants, to capture discretionary upward adjustments in budget planning.
This study yields four main conclusions: First, local governments significantly raise excessive budget revenue targets, especially non-tax revenue targets, when facing higher debt maturity pressure, indicating that non-tax revenue serves as the primary adjustment tool under debt repayment stress. Second, on the expenditure side, budget items closely associated with LGFVs exhibit synchronized growth amid intensifying debt pressure. This reflects that under the “revenue-determined expenditure” fiscal system, the increase in budgeted revenue is mainly used to indirectly support LGFV debt repayment. Third, the study finds a significant downward adjustment in year-end final accounts compared to budget execution, indicating the transfer of fiscal resources. Further verification using LGFV financial statement data confirms that these platforms receive government capital injections at the year-end, corroborating local governments’ supportive actions for LGFV debt repayment. Fourth, micro-level evidence shows that budgetary pressure induced by LGFV debt maturity leads to an increase in firms’ actual non-tax burden, with no significant impact on tax burden, consistent with the macro-level findings.
The main marginal contributions of this paper are threefold: First, it is the first study to systematically identify and empirically verify the “Debt-to-Fee Substitution” effect in the context of local government debt risk research, enriching the literature on the macro and micro effects of local debt risks. Second, it explores the inherent mechanism of structural changes between tax and non-tax revenue in local government budget management under debt repayment pressure, complementing relevant research on budget management. Third, it clarifies the logical chain throughwhich local debt pressure is transmitted via budget targets to push up firms’ non-tax burden, expanding research on non-tax revenue collection and its micro-level effects.
The results indicate the need to strengthen market-oriented debt constraints, enhance budget management transparency and accountability, and regulate non-tax revenue collection to prevent debt risks from spreading to the real economy through budgetary channels. Future research can further analyze the long-term effects of rising non-tax burden on firms’ innovation and productivity, and examine the constraining role of digital governance and fiscal transparency in non-tax revenue expansion.

Research based on Chinese enterprise data reveals that, under open conditions, innovation with Chinese characteristics exhibits typical features of low quality and low disruptiveness. Promoting open innovation and achieving greater self-reliance and strength in science and technology in China are of significant importance for developing new quality productive forces. The institutional opening-up represented by pilot free trade zones (PFTZs) provides a suitable policy shock scenario for evaluating policy effects and the extent to which enterprise innovation is influenced by institutional factors. Most literature directly related to this paper conducts preliminary studies on the mechanisms through which PFTZs affect enterprise innovation behavior, primarily using listed company data or macro-level data. However, limitations in sample representativeness make it difficult to accurately assess the impact of this policy. This study offers a reference for promoting self-reliance and strength in China's scientific and technological innovation under expanding institutional opening-up.
We extend the model of Aghion et al. (2024) by incorporating institutional transaction costs and labor factor structure, revealing the mechanisms through which institutional opening-up affects enterprise innovation behavior. We crawl enterprise latitude and longitude information based on registered addresses and manually collect the geographic boundaries of 53 PFTZ sub-zones for precise enterprise identification. Building on this, we evaluate the innovation effects of PFTZs using datasets on tax surveys, patents, and enterprise recruitment from 2016 to 2020.
The key findings are as follows: (1) PFTZs significantly increase both the quantity and quality of enterprise innovation, with patent applications and citations rising by 1.04% and 0.87%, respectively. A boundary-discontinuity-difference-in-differences (BD-DD) approach based on latitude and longitude verifies the preliminary findings. (2) PFTZs increase the consolidating innovation index by 0.88%, while the impact on disruptive innovation is not significant. (3) PFTZs promote enterprise innovation through positive cost-saving and factor-upgrading effects, and negative competition-intensifying and market-scale effects. (4) Institutional reforms within PFTZs, such as the reduction of negative list items and the replication and promotion of pilot experience, help better realize the innovation-enhancing role of PFTZs. Institutional innovations aligned with local comparative advantages demonstrate stronger positive effects. (5) Extended analyses from spatial technology spillover and enterprise life cycle perspectives show that PFTZ enterprises in mature and decline stages are more inclined towards disruptive innovation.
The marginal contributions are as follows: (1) We manually collect and compile the geographic boundaries of 53 PFTZ sub-zones across 17 provinces and the geographic information of over 440,000 enterprises. Using the ray casting algorithm for assignment judgment and shortest distance calculation, we provide a practical methodological tool for subsequent research. (2) We respectively match the PFTZ negative lists and institutional innovation to the 3-digit industry level and provincial administrative level, constructing two moderating variables: institutional deepening and institutional innovation. This represents an early decomposition of the differential policy effects of various PFTZs on enterprise innovation from a policy intensity perspective. Among these, the institutional coupling index calculated based on institutional innovation and industrial comparative advantage offers a novel perspective for PFTZ performance evaluation. (3) We find that PFTZs reduce institutional transaction costs such as administrative, sales, and financial expenses, while increasing enterprise demand for recruiting high-skilled labor in positions like R&D management. (4) The policy recommendations propose fully leveraging the positive moderating role of institutional deepening and innovation on PFTZs, actively exploring optimized paths for the diversified coupling development of institutional innovation and local comparative advantages, and implementing a PFTZ upgrade strategy from the perspective of institutional opening-up.

The Fourth Plenary Session of the 20th Central Committee of the Communist Party of China has recommended that during the 15th Five-Year Plan period, we should draw on a full range of resources and means to address risks and develop the system for preventing and defusing risks, so as to ensure stable operations in the financial sector. In this context, preventing and mitigating financial risks has become a critical task to ensure economic stability. As both a major source and the ultimate bearer of regional financial risks, the real economy plays a central role in the formation and transmission of the risks. Among the three sectors of the real economy, the non-financial enterprise sector holds the highest macro leverage ratio, and is the primary source of overall financial risk. Its assets (and liabilities) largely correspond to the liabilities (and assets) of the financial sector. When non-financial enterprises face insolvency risk, they may be unable to repay loans, thereby triggering credit risks for financial institutions. In recent years, the widespread adoption of digital technology has driven profound transformations in financial service models. Among these, digital credit, characterized by its immediacy, automation, and remote accessibility, has emerged as an essential tool for financing the real economy. Systematically examining the impact of digital credit development on regional financial risk is thus of substantial theoretical and policy significance for promoting financial support to the real economy and preventing systemic risks.
This study utilizes micro-level data from 5,679 listed non-financial enterprises to construct macro balance sheets and contingent equity balance sheets for 31 provincial-level administrative regions in China. Based on four dimensions:operational risk, liquidity risk, insolvency risk, and market risk, we develop a regional financial risk index using data primarily sourced from the CSMAR database. Unlike existing studies that mainly rely on financial system indicators, this research adopts a microeconomic enterprise perspective to reveal the endogenous mechanisms underlying the generation of regional financial risk, thereby enhancing the effectiveness and forward-looking nature of risk measurement. We then apply a two-way fixed effects spatial Durbin model to empirically examine the direct and spatial spillover effects of digital credit development on regional financial risk during 2011~2022, followed by a mechanism analysis to explore the underlying transmission pathways.
The results reveal three key findings. First, the constructed regional financial risk index effectively captures the impact of macroeconomic shocks on the real economy and financial system. Major events such as the 2015 stock market turbulence and the 2020 COVID-19 outbreak are clearly reflected as significant fluctuations in the index. Second, digital credit development significantly alleviates regional financial risks, not only within local regions but also on neighboring regions through spatial spillover effect, with the mitigating impact accumulating over time. At the risk-dimension level, digital credit primarily operates by easing firms’ operational and liquidity risks. Spatial heterogeneity analysis further indicates the existence of spillover barriers among urban clusters. Third, mechanism analysis shows that digital credit reduces regional financial risk by lowering information asymmetry and enhancing financial competition within regions. Additionally, by strengthening interregional capital flows and trade linkages, digital credit amplifies the spatial spillover of risk mitigation effects.
On the basis of the above results and from a policy perspective, the study suggests: (1) accelerating the construction of infrastructure for digital finance through government investment, fiscal subsidies, and tax incentives to expand coverage and improve service efficiency of digital credit; and (2) promoting the development of digital credit comprehensively, removing administrative barriers, enhancing interregional capital flow and trade linkages, and improving information and capital flow channels to foster deeper integration between the digital and real economies. This would enable digital credit to serve as a sustainable driving force for mitigating regional financial risk.
The contributions of this research are threefold. First, it innovatively constructs a regional financial risk index from the micro perspective of non-financial enterprises, offering a new approach for measuring financial risks, providing a scientific basis for promoting financial support to the real economy and mitigating financial risks. Second, by employing spatial econometric methods, the study systematically examines the cross-regional transmission of the effects of digital credit development on financial risk, advancing research on financial risk spillovers. Third, it reveals both the direct and indirect mechanisms through which digital credit influences financial risk, offering new insights into the formation and transmission of financial risks in the digital era. Future research may further extend this work by incorporating larger and more diverse enterprise samples with longer time spans to test the robustness of the conclusions; obtaining richer regional digital credit data to explore different digital credit models and their risk mitigation effects; and examining the interactions between digital credit and emerging financial forms such as green finance and inclusive finance to build a more comprehensive framework for digital finance and regional risk management.

Population development is a strategic national issue. In advancing the “modernization with a huge population,” miniaturization of household size has become a key feature of China’s demographic evolution. According to the Seventh National Population Census, the average household size in China has declined to 2.62 persons, falling below the long-standing threshold of three persons. This structural shift implies a weakening of the family’s traditional intergenerational support and risk-sharing functions, and profoundly reshapes the underlying logic behind residents’ demand for commercial insurance as a risk management tool oriented toward social mutual aid. Therefore, examining the causal relationship between household miniaturization and commercial insurance demand is essential for understanding household financial behavior, enhancing risk resilience, and improving a multi-tiered social security system.
Accordingly, this paper examines the impact of household size variation and the trendof miniaturization on commercial insurance demand. To address the divergence in existing literature regarding linear relationships, we construct a nonlinear theoretical framework based on the interplay between the “wealth threshold” effect and “altruistic motivation,” proposing an inverted U-shaped hypothesis for the relationship between household size and insurance demand. Empirically, we adopt a combined macro-micro strategy, utilizing provincial panel data (2000–2023) to capture aggregate trends and China Family Panel Studies (CFPS) data (2010–2022) to identify household-level characteristics. Our methodology employs Two-Way Fixed Effects models alongside IV-Probit and IV-Tobit models. To address endogeneity concerns arising from reverse causality, we construct instrumental variables based on lagged divorce rates, exogenous family structure shocks, and fertility policy implementation, thereby ensuring robust and reliable estimation results.
The findings reveal a significant inverted U-shaped relationship between household size and commercial insurance demand, with the inflection point located within the rangeof 3 to 4 persons. Specifically, the demand of miniaturized households significantly exceeds that of non-miniaturized ones, a conclusion that holds after thorough endogeneity treatment and a series of robustness checks. Mechanism analysis identifies two synergistic channels: “strengthening risk protection motivation” and “enhancing household investment capacity,” which demonstrate a transmission logic where motivation drives capacity, and capacity in turn supports motivation. Heterogeneity analysis indicates that the promoting effect of miniaturization strengthens with the householder’s age during mature family stages but weakens in the aging stage. Furthermore, the impact is more pronounced for urban households, households with higher education, and those with better social security coverage. Importantly, the trend toward “individual living” may attenuate the promoting effect of household miniaturization, potentially fostering high-risk solitary households that lack insurance coverage.
Based on the research conclusions, we propose three policy recommendations. First, advance supply-side structural reform of insurance products to accurately meet the full lifecycle needs of miniaturized households. Second, implement tiered policies to address differentiated protection gaps, focusing on the risk exposure of rural, less-educated, and solitary households. Third, strengthen the institutional synergy between “basic social security” and “inclusive commercial insurance”, so as to achieve precise alignment between insurance services and different types of households at their respective development stages.
The marginal contributions of this paper are threefold. First, the research explores a new and timely area. While existing literature predominantly examines household structure from a sociological perspective, this paper employs an economic perspective.Using recent macro-micro data and a nonlinear analytical framework, it identifies the causal effect between household size (primarily its miniaturization trend) and insurance demand, thereby enriching existing research and providing more explanatory theoretical logic and empirical evidence. Second, it deepens the research on transmission mechanisms of miniaturization. Beyond empirically verifying the “strengthened protection motivation” channel, it innovatively identifies the “enhanced investment capacity” pathway and analyzes their synergistic interaction, thus refining the logical chain of how household miniaturization affects commercial insurance demand. Third, it systematically enhances the analytical dimensions. By integrating age structure, family structure, and social security levels into a unified framework, it explores the heterogeneous impacts of household miniaturization, particularly highlighting the effect of the solo-living trend on insurance demand. This provides policymakers with specific pathways to address demographic changes and to optimize a lifecycle-aligned social security system, ensuring an organic alignment between theoretical analysis and policy orientation.

China’s development environment is currently undergoing profound and intricate transformations, characterized by the coexistence of external risks and challenges alongside internal adaptive pressures. As the largest exporter of manufactured goods in the world, China’s industrial capacity utilization rate is inevitably influenced by macroeconomic fluctuations and shifts in foreign demand, necessitating continuous adaption and transformation by firms in response to evolving external conditions. Looking ahead to the 15th Five-Year Plan period, external adverse factors such as uncertainties in the international political and economic landscape persist, coupled with insufficient demand from developed countries, are contributing to renewed risks of overcapacity accumulation. Effectively addressing constraints in external demand and internal pressures of overcapacity will be pivotal to China’s high-standard opening-up during the 15th Five-Year Plan period.
This paper utilizes micro-level industrialfirm data and listed firm data from China to conduct an in-depth investigation into the following questions: First, how do external demand shocks affect firms’ capacity utilization, and what are the underlying mechanisms? Second, do the digital factor inputs help mitigate the negative effects of external shocks? What roles do different types of digital factor inputs play, and through what mechanisms do they operate? By examining these issues, this study aims to provide insights into mitigating external risks, developing the digital economy, and enhancing the resilience of industrial and supply chains. The findings indicate that negative external demand shocks exacerbate the risk of overcapacity, primarily due to a decline in the actual utilization of capacity and insufficient flexibility in adjusting total capacity, which reflects a lack of shock adaptability among firms. Further research reveals that the digital factor inputs can improve firms’ shock adaptability and alleviate the decline in capacity utilization caused by negative external demand shocks. On the one hand, digital transaction inputs assist exporting firms in finding new market outlets for their products when facing negative external demand shocks. On the other hand, the improvement of digital infrastructure accelerates the transformation process of firms in response to changes in the external market environment, including product switching and capacity adjustment.
Based on the existing literature, the potential marginal contribution of this paper lies in the following aspects: In terms of the research perspective, it investigates the impact of external demand shocks on firms’ capacity utilization and analyzes the role of digital factor inputs in mitigating negative external demand shocks, thereby providing a novel perspective for reducing external risks. Regarding indicator measurement, this paper disentangles negative external demand shocks from the broader external demand shock indicators to capture demand contraction originating from downstream product-destination markets more precisely. Furthermore, drawing on the global value chain perspective, it incorporates multi-tiered industrial linkages to construct an indicator measuring the intensity of digital factor inputs.
Based on the research findings of this paper, the following policy implications are proposed: First, continue to deepen the openness of goods and factor flows, further enhance the synergy between domestic and international markets, steadily expand institutional opening-up, align with high-standard international economic and trade rules, and establish a more comprehensive and advanced framework for international cooperation. Second, at the macro level, strengthen the supportive role of the domestic cycle in the economy, advance specialized initiatives to “anti-involution”, and phase out outdated and inefficient capacity. Expand domestic demand, boost consumption, and encourage investment, thereby identifying new drivers of economic growth. At the micro level, enhance the capacity to withstand external shocks and improve supply chain resilience by strengthening resource integration and collaborative management capabilities, optimizing the export structure. Third, fully unleash the growth potential of the digital economy, advance the construction of digital infrastructure and digital platforms, and foster new global digital industrial and value chains. Leverage the digital economy to create diversified markets, develop shared digital economy platforms with other countries and regions worldwide, and strengthen the capacity to respond to global risks.

Market liquidity and price discovery constitute two central dimensions of financial market efficiency (O’Hara, 2003), with adequate liquidity being a necessary condition for efficient price formation. In equity markets, investors hold heterogeneous beliefs: optimistic investors tend to buy, whereas pessimistic investors tend to sell. Liquidity facilitates the aggregation of these heterogeneous opinions by reducing trading frictions. More fundamentally, liquidity is intrinsically linked to the endogenous determination of marginal price setters, namely, which investors’ beliefs ultimately get reflected in market prices.
Leverage reshapes this equilibrium by altering marginal investors. Optimistic investors above the marginal type can long through margin financing, while pessimistic investors below the marginal type can short to express negative views. When markets are sufficiently liquid and long-short participation is balanced, both bullish and bearish beliefs can be incorporated into prices in a relatively symmetric manner, enhancing price efficiency. In contrast, under limited liquidity, information may still enter prices but often in an asymmetric and distorted manner. When optimistic investors dominate trading activity, leveraged buying amplifies one-sided price pressure and weakens the disciplining role of opposing beliefs.
This mechanism becomes particularly salient during economic expansions, when market-wide optimism prevails. In upswings, optimistic investors increase leverage to scale up purchases, amplifying price appreciation. Rising asset prices, in turn, relax collateral constraints and support higher leverage, reinforcing the influence of optimistic beliefs on prices. This positive feedback loop can exacerbate liquidity risk: when investors’ beliefs converge and trading is dominated by liquidity demand rather than supply, the scarcity of sellers may cause market liquidity to deteriorate.
Motivated by these considerations, this paper addresses three interrelated questions. First, how does market liquidity behave when asset prices are primarily driven by optimistic beliefs? Second, do margin trading and short selling exert symmetric effects on liquidity? Third, how do these effects evolve over market cycles, and through which information channels do they operate?
In an idealized setting with balanced long-short participation, margin trading and short selling together constitute a symmetric belief-expression mechanism: margin trading allows optimistic investors to lever up long positions, while short selling enables pessimistic investors to express bearish views. Under such conditions, heterogeneous beliefs are more fully incorporated into prices, improving both pricing efficiency and liquidity. In practice, however, margin trading and short selling are highly asymmetric. Margin financing volumes vastly exceed short-selling activity, resulting in a “one-sided leverage” market structure. In such an environment, optimistic beliefs can be disproportionately amplified and belief convergence may be intensified, while liquidity pressure may rise during market upswings, undermining overall market efficiency.
China’s introduction of margin trading and short selling in 2010 provides a unique quasi-natural experiment to examine these mechanisms. Using daily data on A-share stocks from 2009 to 2015, we employ a difference-in-differences (DID) framework to identify the causal effects of margin trading and short selling on stock-level liquidity. We find that, in the long run, the introduction of margin trading and short selling reduces the liquidity of eligible stocks. Decomposing the effects reveals pronounced asymmetry: margin financing significantly impairs liquidity, whereas short selling improves liquidity. Because margin financing overwhelmingly dominates trading activity, its negative effect drives the aggregate outcome. Moreover, the adverse liquidity effect is substantially stronger during bullish periods, consistent with asymmetric trading constraints that amplify liquidity imbalances in such periods. Mechanism analyses further show that margin trading, particularly margin financing, reduces stock price information efficiency and suppresses information production. The suppression of pessimistic information is especially pronounced during bullish periods. In addition, firms with higher default risk exhibit stronger incentives for information production and rely more heavily on private information to mitigate potential losses, highlighting substantial heterogeneity in firms’ informational responses.
This study contributes to the literature along three dimensions. First, at the theoretical level, existing research has largely progressed along two separate lines: one emphasizing the role of leverage and collateral constraints in asset pricing, the other examining how heterogeneous investor beliefs affect market efficiency. These two lines overlook their intrinsic linkages. This paper bridges these strands by integrating the collateral theory (Geanakoplos, 2010) with the heterogeneous-belief asset pricing model (Hong and Stein, 2003), providing a unified framework that explains how collateral constraints regulate belief expression in prices and generate asymmetric liquidity effects over the business cycle. Second, at the empirical level, the paper exploits China’s institutional setting and the 2010 margin trading reform to implement a clean identification strategy, avoiding cross-country confounding factors related to institutional and cultural heterogeneity. This approach provides systematic evidence on the structural relationship among leverage, information, and liquidity, and documents their cyclical asymmetries. Third, in terms of policy relevance, the findings deepen our understanding of market microstructure and offer implications for macroprudential regulation. Structural constraints in China’s capital market, particularly the imbalance between long and short mechanisms and limited securities lending supply, remain binding, and the “one-sided leverage” structure persists. More broadly, the leverage-information-liquidity framework developed in this paper provides a useful lens for analyzing liquidity and risk transmission in other leveraged financial markets, including bonds, foreign exchange, and derivatives.

The importance of supply chain information disclosure and supply chain corporate social responsibility (CSR) is increasingly prominent. From the perspective of policy orientation, the scope of information disclosure regulations has gradually expanded to the supply chain dimension. Both the United States and the European Union have enacted policies to conduct due diligence on supply chains, requiring enterprises to disclose environmental and social risks within their supply chains and emphasizing social responsibility issues such as environmental protection and labor rights in the supply chain. From the perspective of enterprise practice, whether suppliers meet social responsibility requirements is essential for the sustainability of the supply chain. Good social responsibility performance has become a key factor for customer enterprises in selecting and evaluating supplier partners. However, there is no direct requirement for supply chain disclosure currently in China’s mandatory CSR information disclosure policies, and existing research has focused solely on the impact of mandatory CSR information disclosure policies on the enterprises themselves. Therefore, further evaluating the supply chain spillover effects of existing disclosure policies and analyzing the mechanisms by which mandatory customer CSR information disclosure influences suppliers’ CSR performance are of great practical significance for the development of sustainable supply chains.
Based on supply chain data and corporate social responsibility data provided by the CSMAR database from 2008 to 2021, this paper empirically examines the supply chain spillover effects and mechanisms of mandatory customer CSR information disclosure from the perspective of suppliers. Based on stakeholder theory and resource dependence theory, this paper constructs an analytical framework for the impact of mandatory customer CSR information disclosure on suppliers’ CSR performance, and combines organizational legitimacy theory and signaling theory to analyze the two channels of supply chain spillover effects: “supply chain compliance pressure” and “supply chain financial support”. The study found that mandatory customer CSR disclosure has a spillover effect on suppliers’ CSR performance. This spillover effect is mainly driven by “supply chain compliance pressure” and “supply chain financial support” channels. Among them, the “supply chain compliance pressure” channel is mainly reflected in the evaluation, screening, and management of suppliers by customer enterprises after being required to disclose corporate social responsibility information, adopting a diversified supply chain configuration mode to transmit the compliance pressure of improving CSR performance to the suppliers. In this context, when suppliers have a higher level of customer dependence, supply chain compliance pressure more significantly boosts suppliers’ CSR performance. The “supply chain financial support” channel reveals that when customer enterprises are required to disclose CSR information and the suppliers have a higher level of customer dependence, the financing credit enhancement from customer enterprises alleviates suppliers' external financing constraints to improve suppliers’ CSR performance. Heterogeneity analysis reveals that the supply chain spillover effect of mandatory customer CSR disclosure is more pronounced when suppliers have a lower level of industry competition, a higher level of digital transformation, and higher transparency in supply chain relationships. Extended analysis reveals that this spillover phenomenon only currently exists at the level of first-tier suppliers. Furthermore, this spillover effect is asymmetric. Mandatory supplier CSR disclosure does not have supply chain spillover effects on customer enterprises. Finally, there is also no supply chain spillover effect when customer enterprises voluntarily disclose CSR information.
This paper proposes the following policy recommendations: First, accurately identify the actors responsible for mandatory disclosure policies, stimulate their exemplary role in CSR performance, promote upstream transmission of CSR disclosure guidance from customer enterprises to suppliers, and encourage listed companies to gradually focus on and improve their performance in CSR and sustainable development. Second, establish unified standards for CSR information disclosure and CSR performance evaluation, encourage listed companies to disclose information on their supply chain CSR performance, and promote sustainable CSR development throughout the supply chain.
The possible marginal contributions of this paper are: First, it broadens the scope of CSR research from a supply chain perspective, extending the corporate boundary of CSR governance to the entire supply chain, which is a valuable supplement to CSR research. Second, based on the perspective of supply chain responsibility, this paper expands the research on the mechanisms of supply chain spillover effects through two channels: “supply chain compliance pressure” and “supply chain financial support.” Third, this paper analyzes the supply chain spillover effects of CSR from multiple dimensions, clarifies the heterogeneous impact of supplier enterprise characteristics and supply chain relationship characteristics on supply chain CSR spillovers, enriches the understanding of the level and direction of supply chain CSR spillovers, and clarifies the differential impact of mandatory disclosure and voluntary disclosure on supply chain spillover effects for customer enterprises.

In contrast to existing literature that primarily focuses on Initial Public Offerings (IPOs), this study examines the impact of investor-underwriter relationships on investor bidding behavior in the Chinese Private Investment in Public Equity (PIPE) auction market. Financial investors in PIPEs confront a trade-off between the allocation probability and subscription cost in auctions. Typically, a higher bid price increases the chance of allocation. Nevertheless, given the stock’s intrinsic market value, a high bid price can increase subscription costs and reduce post-allocation profits. PIPE auctions operate under a non-discriminatory pricing method. The allocated investors subscribe to PIPE shares at the same issuance price, which is set based on the offering price quoted by the last investor allocated shares. Lead underwriters are more inclined to convey accurate information about the PIPE issuer to financial investors with whom they have close relationships. These investors are information arbitrageurs who capitalize on their informational edge to secure more favorable allocations. Conversely, investors without such access may inflate their bids to boost allocation chances.
Using manually-compiled data on PIPE events and investor bidding in the Chinese market from January 1, 2016, to June 30, 2021, we find that the bidding premiums of financial investors closely related to underwriters are significantly lower. These financial investors are also more likely to acquire shares in PIPEs successfully. Moreover, the issuance discount is larger when they participate in PIPEs.
We analyze the mechanism of this effect in several ways. We argue that financial investors with close ties to lead underwriters can accurately interpret investment recommendations from the underwriters’ analysts. Their information advantage is particularly valuable for firms with overly optimistic stock recommendations issued by PIPE underwriters’ analysts to facilitate underwriting business. We find that the bidding premium differences between those financial investors with close connections to the underwriters and those without are significantly lower for this subsample of firms. Similar lower bidding premium differences are observed in the subsample of firms with more earnings management, increased corporate violations, and deficient corporate governance.
Informed financial investors have incentives to quickly profit from the information they acquire from the PIPE underwriters. We find that they can borrow pre-listing shares and sell them at a premium in the secondary market while subscribing to discounted PIPE shares. Financial investors with solid underwriter relationships are more likely to collaborate with the lead underwriter in executing a PIPE short-selling arbitrage strategy. This strategy allows them to realize the issuance discount between the market and issuance prices in advance, thereby securing short-term profits.
Our study contributes to the literature by examining the influence of investor-underwriter relationships on investor bidding behavior within the Chinese auctioned PIPE market, characterized by substantial fundraising and a distinct pricing mechanism. Previous studies on IPOs had inconsistent results regarding bid levels, with some indicating higher bids due to stronger relationships (Huang et al., 2008; Jiang et al., 2022; Luo et al., 2023) and others suggesting the advantages of lower bids (Reuter, 2006; Binay et al., 2007; Henderson and Tookes, 2012). Our study, however, proposes that investors with solid ties to underwriters gain an informational edge, which results in lower bidding premiums in PIPEs. This insight addresses a significant gap in the current understanding of the PIPE market.
Using manually-collected detailed investor bidding data, we explore the behavioral differences arising from relationship-driven information asymmetry. As information arbitrageurs, financial investors with close ties to lead underwriters enjoy higher allocation probabilities and more substantial issuance discounts. Additionally, their collaboration with lead underwriters in employing PIPE short-selling arbitrage strategies allows for the preemptive capture of issuance discounts and the realization of arbitrage profits. Investors lacking information may reluctantly inflate their bids to boost allocation chances. We use a large sample size and reveal more generalized insights beyond the specific case, which enhances theoretical and practical guidance.
Our findings offer several policy implications for policymakers. Regulators should closely monitor the dynamics between investors and lead underwriters in PIPE transactions and their influence on bidding practices. It is imperative to regulate PIPE short-selling arbitrage strategies and effectively oversee the conduct of investors, underwriters, and market participants. Concurrently, policymakers should enhance market transparency to mitigate information arbitrage and free-riding caused by information asymmetry.