Using Chinese provincial panel data, this paper examines how climate transition risk (CTR) shapes the inflation term structure and inflation vulnerability. The results indicate three main findings. First, CTR has clear phase-dependent effects: it pushes inflation up in the short term but significantly dampens inflation over the medium to long term. Second, quantile estimates show strong asymmetry. CTR increases inflation in the lower quantiles while reducing inflation in the upper quantiles, suggesting that CTR may raise near-term inflation pressure but lowers the probability of extreme inflation outcomes and, in turn, supports macroeconomic stability. Third, CTR significantly affects both downside and upside inflation vulnerabilities. It also interacts with economic shocks, and these interactions jointly amplify inflation vulnerability.
Drawing on panel data from 31 Chinese provinces covering the period 2011–2022, this paper employs a System GMM model to empirically examine the impact mechanisms of digital inclusive finance and its three sub-dimensions (coverage breadth, usage depth and digitalisation level) on economic resilience. The findings reveal that, firstly, digital inclusive finance significantly enhances economic resilience overall, a conclusion that remains valid following a series of robustness tests;among its sub-dimensions, the driving roles of coverage breadth and usage depth are particularly prominent, whilst the direct effect of digitalisation is not yet significant. Second, the examination of the impact mechanisms indicates that digital inclusive finance can enhance economic resilience through two pathways: increasing R&D intensity and stabilising social consumption levels. Third, the level of innovation plays a positive moderating role between digital inclusive finance and economic resilience, suggesting that innovation is a key factor in amplifying the effects of financial empowerment.Fourthly, the energy structure exhibits a significant double-threshold effect, and its optimisation helps to enhance the resilience-boosting effects of digital inclusive finance. Furthermore, the impact of digital inclusive finance exhibits marked regional heterogeneity, displaying a gradient that decreases from east to west. The study recommends optimising the structural supply of digital inclusive finance, strengthening innovation-driven development, promoting its synergistic development with energy transition, and implementing regionally differentiated policies to systematically enhance economic resilience.
SRDIs (Specialized, Refined, Differential, and Innovation enterprises) are increasingly recognized as essential contributors to the high-quality development of the manufacturing industry. Based on a micro-innovation ecosystem perspective, this study explores diverse pathways for enhancing total factor productivity (TFP) of these enterprises. We combine Necessary Condition Analysis and fuzzy-set Qualitative Comparative Analysis to examine the complex causal mechanisms underlying their success. The study reveals the following findings: (1) Among manufacturing SRDIs, high TFP is jointly enabled by industrial environmental complexity, regional economic development, government subsidies, innovation capability, knowledge absorptive capacity, and employee educational attainment; however, no single factor constitutes a necessary condition. (2) Six configurations exist within specific micro-innovation ecosystems that effectively drive high TFP, a conclusion that remains valid following robustness testing. (3) Across nearly all configurations, high government subsidies do not significantly contribute to high TFP, an effect that is particularly pronounced among manufacturing SRDIs in eastern regions.
Characterized by innovativeness and proactiveness, entrepreneurial spirit has consistently served as a key driving force behind China’s economic transformation, directly influencing the level of corporate risk-taking. However, the intrinsic link between entrepreneurial spirit and corporate risk-taking has not yet been fully revealed. Drawing on a sample of 12,636 firm-year observations from A-share listed companies on the Shanghai and Shenzhen stock exchanges over the period from 2014 to 2023, this study investigates the impact of entrepreneurial spirit on corporate risk-taking behavior, as well as the moderating role of internal control effectiveness in this relationship. Empirical results indicate that a higher level of entrepreneurship is associated with a stronger propensity for corporate risk-taking, and that robust internal controls can moderate the positive effect of entrepreneurial spirit on risk-taking behavior. Further analysis reveals that innovation capability, entrepreneurial spirit, and entrepreneurial talent are key factors driving this effect. This association is particularly pronounced in state-owned enterprises (SOEs), where higher entrepreneurial levels correspond to greater risk-taking propensities, and also in the manufacturing sector, where innovation-intensive strategies exacerbate corporate risk exposure. By constructing and quantifying a comprehensive evaluation system for entrepreneurial spirit, this study not only enriches the theoretical framework in the fields of entrepreneurship, innovation intensity, and risk management, but also provides both theoretical and practical implications for policymakers and enterprises seeking to promote innovation-driven sustainable development.
Population aging poses a fundamental challenge to established business models, compelling firms to adapt their strategic resource allocation. This paper explores how population aging affects enterprises’ decisions regarding cross-regional investment. Based on a sample of Chinese listed firms, we document that population aging exerts a significantly positive effect on enterprises’ cross-regional investment activities. This effect operates mainly through two mechanisms: surging labor costs and binding financing constraints. In addition, our heterogeneous analysis reveals that the aging effect is substantially stronger for small and medium-sized enterprises, labor-intensive firms, and businesses with low innovation intensity. Lastly, we demonstrate that cross-regional investment yields more pronounced risk mitigation and greater growth capacity enhancement for firms in high-aging regions relative to their counterparts in low-aging regions.
While existing research has extensively examined the environmental benefits of digital technologies, considerably less attention has been paid to how environmental pollution constrains their diffusion. Leveraging regional air pollution disparities across China, this study examines firm-level digitalization divergence. Linking comprehensive data from listed firms with prefecture-level metrics, we find that heightened pollution exposure significantly impedes digital transformation, eroding both the breadth and depth of technology adoption. Pollution-driven talent flight is a key underlying mechanism. Although firms temporarily replenish talent through autumn campus recruitment, such measures are unsustainable. Critically, such talent flight is not inevitable; high-skilled workers’ relocation decisions are moderated by affective ties (e.g., Confucian ethos, family bonds, governance expectations) and economic incentives. Furthermore, climate physical risks amplify pollution-induced digital divides, disproportionately trapping low-resilience firms in a trilemma of pollution, climate physical risks, and digital stagnation. This study provides micro-evidence on the interplay of environmental degradation, talent mobility, and digital inequality, suggesting that overlooking the human capital crowding-out effect of pollution may compromise the effectiveness of technology-driven green transition policies.
Emerging-market startups face substantial information frictions when diffusing innovation in developed economies. We examine whether cross-border venture capital (VC) alleviates these frictions. China provides an empirical laboratory where strong domestic innovation coexists with pronounced cross-border verification barriers, enabling identification of the certification role of foreign financial intermediaries. Using data on Chinese startups with U.S. patent filings from 2001 to 2023, we estimate the causal effect of U.S. venture capital backing on U.S. knowledge adoption, measured by forward citations from U.S. firms. Exploiting matching and quasi-experimental variation in U.S. VC supply and geopolitical shocks, we find that U.S. VC-backed startups experience approximately 20 % higher U.S. citation outcomes relative to comparable startups without U.S. VC participation. The effect is stronger when CEOs have foreign experience. These findings suggest that sustaining cross-border equity ties is critical for preserving global innovation diffusion amid rising geopolitical fragmentation.
In the context of global financial integration, risk contagion among small and medium-sized financial institutions (SMFIs) poses a prominent regulatory challenge. Online public opinion has become a key channel for cross-market risk transmission. Based on DeepSeek and FinBERT, this paper constructs an influence-weighted three-dimensional index of online public opinion. Using daily data of 45 listed small and medium-sized financial institutions, we adopt the time-varying parameter stochastic volatility vector autoregressive model (TVP-SV-VAR) model to analyze the dynamic impacts of online public opinion on systemic risks. The empirical results indicate that the impacts of online public opinion are asymmetric and time-varying, with short-term disturbances far stronger than those in the medium and long run. Investor sentiment presents bidirectional fluctuations and notable stage differences, while market divergence continuously exacerbates systemic risks. In terms of transmission effects, significant industrial differentiation exists. The diversified financial sector is most sensitive to online public opinion, the banking sector shows strong risk resistance, and the insurance sector exhibits phased risk fluctuations. This research provides empirical evidence for improving financial risk early warning systems and implementing differentiated supervision over online public opinion. Nevertheless, restricted by data availability, our sample only covers listed small and medium-sized financial institutions. Follow-up studies could further explore the applicability of the research conclusions to non-listed institutions.
As an increasingly frequent external uncertainty shock, the impact of extreme weather shocks on the labor market has been extensively discussed, whereas few studies have examined the consequences from the perspective of the employment structure. Focusing on the employment structure of enterprises, this study utilizes the data of World Bank Enterprise Survey in China (2024) and analyzes the employment strategies adopted by enterprises in the face of extreme weather shocks. Empirical evidence indicates that under extreme weather shocks, the practices of non-standard employment (NSE) among enterprises have increased significantly. To better explain this observation, the study provides suggestive evidence for two potential channels of production interruptions and capacity underutilization. Specifically, extreme weather shocks tend to contribute to production disruptions and idle capacity, which may subsequently incentivize enterprises to adopt adaptive behaviors of increasing NSE to reduce costs and enhance operational flexibility. Further analysis reveals significant heterogeneity in the impact of extreme weather shocks, with more pronounced effects observed among small and medium-sized, low labor-regulated, low-reputation, and non-exporting firms. Finally, NSE practices adopted by enterprises in response to extreme weather shocks are found to come at the expense of employment stability and human capital accumulation. This study offers a novel perspective on NSE practices and provides new insights for climate policy formulation.
In the context of China’s economic transition, the determination of firm boundaries is shaped not only by production efficiency but also by informal contracts and the financial institutional environment. Exploiting the quasi-natural experiment of the policy "combining Technology with Finance," this paper employs a multi-period difference-in-differences (DID) approach to examine the impact of the policy on firm vertical specialization. The empirical results demonstrate that the Tech-Fin pilot significantly promotes corporate specialization—a finding that remains robust across parallel trend tests, placebo tests, and various sensitivity analyses. Mechanism analysis reveals that the policy empowers firms through two primary channels: first, by reducing external transaction costs through an optimized contracting environment; and second, by enhancing supply chain stability, utilizing financial instruments to strengthen the credit nexus between core enterprises and their partners, thereby curbing motives for inefficient "defensive" vertical integration. Heterogeneity analysis shows that the promotional effect is more pronounced among firms facing high financing constraints, private enterprises, and those in high-tech industries. This research provides critical micro-level evidence on how Tech-Fin innovation empowers the real economy and offers policy insights for optimizing industrial structures and advancing division of labor.
Local government debt has long been an important financing tool in China, with heterogeneous effects across regions and over time. Combining prefecture-level empirical evidence with a heterogeneous-agent general equilibrium model, this paper studies the macroeconomic and welfare implications of alternative local government debt-to-GDP ratios. The empirical results show that, in the short run, debt exhibits an inverted U-shaped effect on output, consumption, and investment, with stronger nonlinear responses in less developed regions. We then calibrate the model separately for developed and less developed regions to quantify long-run outcomes. The quantitative analysis indicates that, under the current fiscal framework, higher debt ratios lead to monotonic declines in output, consumption, and private investment, rising interest rates, and worsening wealth inequality, resulting in lower household welfare. Regional heterogeneity arises from differences in capital productivity, fiscal capacity, and exposure to crowding-out effects. Overall, the findings highlight that once local government debt becomes a binding constraint, its expansion primarily amplifies macroeconomic distortions rather than supporting growth, providing policy-relevant insights for managing local debt risks in China.
Global agriculture faces the dual challenge of ensuring food security and reducing carbon emissions. Digital transformation is regarded as a key driver in reshaping agricultural production modes and synergizing the United Nations Sustainable Development Goals of Zero Hunger (SDG2) and Climate Action (SDG13). This study constructs a multidimensional Subject-Tool-Industry index system to measure agricultural digital transformation (ADT) and employs the EBM model to assess agricultural carbon efficiency (ACE). Based on panel data from 30 provincial-level regions in China (2012–2022), we empirically investigate the impact of ADT on ACE. The findings indicate that ADT has a significant positive impact on ACE, a conclusion that remains valid after a series of robustness checks. Mechanism analysis reveals that agricultural socialized services act as a key mediating channel for this promotion. Furthermore, advanced industrial structure exerts a positive moderating effect, while digital inclusive finance demonstrates a threshold effect where the benefits materialize only after financial development exceeds a specific level. Heterogeneity analysis demonstrates that the driving effect is more pronounced in major grain-producing areas and regions with high concentrations of new agricultural business entities. Additionally, the study confirms that ADT generates significant positive spatial spillovers. This study provides a valuable reference for developing economies seeking low-carbon transition paths.
This paper estimates the time-varying welfare cost of inflation (WCI) in India from 1996Q1 to 2024Q1. The objective is to analyse how WCI has evolved over time, particularly across the pre- and post-inflation targeting approach (ITA). The results reveal significant variation in WCI over the sample period, largely driven by changes in the sensitivity of money demand. In the pre-ITA period, high interest rates, along with high interest elasticity, contributed to elevated WCI. However, in the post-ITA period, WCI increased despite a decline in interest rates. This is primarily attributed to high interest elasticity of money demand, implying that a reduction in inflation or interest rates does not automatically translate into lower welfare losses. These findings suggest that policymakers need to focus more on the underlying structural, institutional and behavioural factors to effectively reduce the WCI.
What is the relationship between non-means-tested welfare programs (i.e., basic medical insurance) and charitable giving? This study addresses this question by examining the causal effect of the urban-rural medical insurance integration reform on charitable giving among rural households in China. Using data from the China Health and Retirement Longitudinal Study and a difference-in-differences strategy, we evaluate the impact of the reform. The results show that the URMII reform increases the unconditional amount of charitable giving among rural households by an average of 59.007 yuan. This positive effect is mainly driven by the extensive margin, with the reform increasing the probability of charitable giving by 6.2 percentage points, while having no statistically significant effect on the intensive margin of donation amounts. Mechanism analyses suggest that the reform promotes charitable giving primarily by reducing precautionary savings and enhancing life satisfaction. The positive effect is also found to be more pronounced among rural households with younger and better-educated household heads, as well as those with fewer children. Overall, the evidence highlights the role of health-related welfare programs, specifically the urban-rural medical insurance, in promoting charitable giving in rural China.
Private investment is often constrained by uncertainty over the credibility of government support. Using variation in the strength of disclosed support across 12,595 governmentpromoted projects in China, we examine how differences in support signals relate to private capital participation under a unified disclosure regime. Stronger signals correspond to a 1.1-1.6 percentage-point higher probability of successful promotion, relative to a 3.3 percent baseline. Stronger signals are further linked to lower perceived property-rights and policy risks and to a shift in investor participation toward longer-term, more committed forms. These patterns are more pronounced for projects with weak market orientation and high dependence on government action. Fiscal constraints are associated with a weaker role for policy signals, whereas prior experience with public-private cooperation and more favorable business environments are associated with a stronger role. Together, these results indicate that institutional quality shapes the effectiveness of policy signals in crowding in private investment.
To address the extreme and asymmetric effects observed in financial market volatility, this paper proposes an improved real-time GARCH-MIDAS model for volatility forecasting and risk measurement in the renewable energy sector. Specifically, mechanisms capturing these extreme and asymmetric effects are integrated into both the long-term and short-term components of the model, strengthening its capacity to predict future volatility and risk. First, we extend the traditional real-time GARCH-MIDAS model by constructing a family of real-time GARCH-MIDAS models capable of capturing various volatility characteristics. Second, we mathematically derive the maximum likelihood estimation for model parameters and comprehensively explain the calculation process for Value at Risk (VaR). Finally, numerical simulations and empirical analyses are conducted to validate the effectiveness of the proposed model. Simulation results demonstrate that the improved model provides a superior fit for data exhibiting extreme and asymmetric effects. Empirical results further confirm that the VaR values calculated using the proposed model pass backtesting successfully, enhancing the accuracy of volatility forecasting and risk measurement. Consistent with these findings, the real-time GARCH-MIDAS model incorporating extreme and asymmetric effects addresses the limitations of the traditional models in fitting financial data, thereby advancing its application in volatility forecasting and regulatory risk assessment for the renewable energy sector.
