Search Results (105)

This study asks whether, and through which firm-level channels, the green data center (GDC) pilot improves corporate sustainability, and it aims to quantify the policy effect and identify its transmission pathways. Under the dual shift in digital transformation and low-carbon transition, the energy demand and emissions generated by data centers have become important constraints on the sustainability performance of firms. This study regards the 2015 “National Green Data Center Pilot Work Plan” as a quasi-experimental policy shock. In terms of methods, using panel observations of Chinese A-share companies listed in Shanghai or Shenzhen during 2010–2024, a difference-in-differences (DID) strategy is employed to estimate the effect of GDC policy and to identify its transmission pathways for corporate sustainability. In terms of results, the empirical estimates indicate that the GDC pilot improves corporate sustainability, and the effect is robust to fixed-effects specifications, an instrumental-variable strategy, propensity-score matching, and a placebo test. Mechanism tests show that the pilot works through three channels: greater green innovation output and technical value, reduced financing frictions, and enhanced green governance capacity. Heterogeneity tests further show that the effect is stronger among firms with a higher level of digital transformation, a larger share of skilled technical personnel, stronger internal control, and greater executive green awareness, and that it is clearer where regional environmental regulation is stricter and market competition is more intense. In terms of conclusions, by integrating institutional pressure theory with the resource-based view, this study explains how the GDC pilot is translated into a firm-level sustainability advantage, and it offers evidence for refining GDC policy design and advancing the coordinated digital and green transformation of enterprises. The novelty of the study lies in providing firm-level causal evidence within a unified “pressure-to-capability” framework, in opening the three transmission channels, and in specifying the technological, organizational, and environmental conditions under which the effect is stronger. Full article

The realization of forest ecological product value has been promoted as an important pathway for reconciling ecological conservation with rural prosperity. However, it remains unclear whether the growth of forest ecological product value has been synchronized with improvements in farmers’ livelihoods. Using panel data from 31 Chinese provinces from 2011 to 2022, this study develops an integrated framework combining allometric growth analysis, a Bayesian hierarchical symbiotic coefficient model, a Lotka–Volterra interaction model, a multi-period difference-in-differences design and LightGBM-SHAP interpretation. The results show that 87% of provinces exhibit negative allometric growth, indicating that forest ecological product value has generally grown faster than farmers’ income. The national symbiotic coefficient increased before 2019 but declined thereafter, suggesting a weakening ecological-livelihood synergy. The multi-period DID results indicate that the 2017 Green Finance Reform and Innovation Pilot Policy significantly weakened the symbiotic relationship in pilot provinces. LightGBM-SHAP further shows that financial development, technological progress and transportation infrastructure are key variables associated with symbiotic equilibrium, with substantial regional heterogeneity. These findings suggest that ecological product value realization and green finance do not automatically translate into inclusive livelihood benefits. More targeted benefit-sharing, financial transmission and farmer-participation mechanisms are needed to promote forest-based ecological prosperity. Full article

Reconciling pollution–carbon reduction with green growth is a central challenge for sustainable urban transition, yet the role of innovation-oriented financial policy in this process remains insufficiently understood. This study uses China’s sci-tech finance pilot policy (STFP) as a quasi-natural experiment and applies a multi-period difference-in-differences model to panel data for 284 prefecture-level cities from 2008 to 2023. The baseline results show that STFP significantly reduces the pollution–carbon synergistic pressure index (PCSP) and improves the green growth efficiency index (GGEI). Specifically, the policy reduces PCSP by approximately 8.10% and increases GGEI by 0.0350 units. These conclusions hold after a series of robustness and endogeneity tests. Mechanism analysis reveals that STFP works through three pathways: stimulating green industrial entrepreneurship, promoting green and digital technological innovation, and inducing the agglomeration of capital, talent, and technology factors. Heterogeneity analysis shows that the policy effect is more pronounced in large cities, cities with stronger collaborative governance capacity, and cities with better innovation environments. Spatial analysis reveals that STFP significantly reduces PCSP in neighboring cities, but has no significant spatial spillover effect on GGEI. Further analysis shows that STFP strengthens the coordinated improvement of pollution–carbon reduction and green growth. Policy-interaction analysis indicates that the Zero-Waste City pilot enhances the effect of STFP, whereas green finance policy exhibits a marginal substitution effect. This study provides city-level evidence on how sci-tech finance can serve as an institutional instrument for coordinating environmental governance and green growth in sustainable urban transition. Full article

The rapid growth of computing demand poses a material challenge to climate policy, making the productivity effects of green digital infrastructure an urgent empirical question. This study estimates whether China’s National Green Data Center Pilot Program, a policy bundling energy efficiency mandates with renewable energy procurement at the infrastructure layer, generates measurable firm-level effects on digital transformation and total factor productivity (TFP). This study treats the staggered rollout of the program across cities as a quasi-natural experiment and estimates its effect on listed firms using a two-way fixed effects difference-in-differences design over 2016 to 2023, complemented by event study analysis, placebo tests, instrumental variable diagnostics, heterogeneity robust estimators for staggered adoption, and mechanism and moderation analyses. The central finding is that pilot designation significantly accelerates firm-level digital transformation, measured by textual indicators of data value mining capability ($p<0.01$), which remains significant across specifications. Complementary evidence points to a modest positive effect on TFP, with an estimated increase of approximately 2.0 percent under the preferred city-level clustered specification, interpreted as suggestive evidence rather than the sole basis for inference. Exploratory mediation decomposition under the strong assumption of sequential ignorability indicates that digital transformation accounts for approximately 23.5 percent of the total effect, though this estimate should be treated as indicative rather than definitive. Mechanism-consistent analysis finds a marginally significant positive association with corporate ESG performance ($p<0.10$), while the association with green technology innovation is directionally positive but not statistically distinguishable from zero. Moderating effect analysis reveals that financing constraints and leverage significantly attenuate the productivity dividend, while public environmental concern provides a marginally significant amplifying effect ($p<0.10$). These results position green data center policy primarily as an upstream enabler of digital transformation that can generate productivity benefits when firms possess sufficient complementary investment capacity. Full article

The environmental effects of green finance policies involve complex systemic interactions across multiple levels, yet existing studies often adopt fragmented analytical approaches. Drawing on the multi-level perspective (MLP), this study conceptualizes the environmental impacts of Green Finance Reform and Innovation Pilot Zones (GFRIPZs) as a process of systemic green transformation involving interactions among landscape, regime, and niche levels. Using panel data of 287 prefecture-level and above cities in China from 2012 to 2022, this study applies a staggered difference-in-differences (DID) model to evaluate the environmental impacts of GFRIPZs. The results show that GFRIPZs significantly reduce both PM_2.5 concentrations and CO₂ emissions. Mechanism analyses based on multiple mediation models and GSEM reveal pollutant-specific differences in underlying channels. Green technological innovation (GTI) constitutes one observable pathway for PM_2.5, whereas the policy effect is more closely associated with energy structure adjustment for CO₂. Heterogeneity analysis further shows that PM_2.5 mitigation is stronger in colder cities, while CO₂ reduction is more pronounced in developed cities. These findings reveal pollutant-specific mechanisms of green finance and offer policy implications for developing countries seeking to promote systemic green transformation. Full article

The transition toward sustainable manufacturing requires an understanding of how industrial policies shape firms’ long-term green innovation capabilities. This study investigates the impact of China’s intelligent manufacturing pilot policy on enterprises’ sustainable green innovation, conceptualizing the policy as an exogenous driver of systemic transformation at the firm level. Using multi-period difference-in-differences (DID) regression on an unbalanced panel dataset of Chinese listed companies from 2010 to 2023, we find that the intelligent manufacturing pilot policy exerts a significantly positive effect on enterprises’ sustainable green innovation. Mechanism analyses reveal that the policy promotes sustainable green innovation through three pathways: facilitating digital transformation, alleviating financing constraints, and enhancing ESG performance. Heterogeneity analysis further indicates that the policy effects are more pronounced in eastern regions, among non-state-owned enterprises, in non-heavily polluting industries, and in technology-intensive industries. These findings provide insights into how systemic policy interventions can drive sustainable innovation at the firm level, with implications for policymakers and enterprises seeking to align industrial upgrading with long-term green development. These findings are interpreted through a system transformation lens, where intelligent manufacturing policies trigger co-evolutionary changes across digital, financial, and governance subsystems. Full article

Against the backdrop of carbon peaking, carbon neutrality, and digital economy development, exploring the pathways through which artificial intelligence (AI) applications in manufacturing enterprises empower green transformation is of great significance. Using panel data on Chinese A-share listed manufacturing companies from 2005 to 2024 and a difference-in-differences (DID) model, this study examined the impact of the National Artificial Intelligence Innovation and Application Pilot Zones (AI Pilot Zones) policy on corporate green innovation. The results showed that the establishment of AI Pilot Zones significantly promoted green innovation among manufacturing enterprises, and this conclusion remained robust after parallel trend tests, PSM-DID estimation, and alternative variable measurements. Mechanism analysis revealed that financing constraints served as a key mediating channel, and that AI policies promoted green innovation through a serial mediation mechanism involving fintech development and the alleviation of financing constraints. Moderation analysis indicated that both human capital and digital transformation enhanced the policy effect. Heterogeneity analysis suggested that the policy’s impact was more pronounced among non-state-owned enterprises, large enterprises, and firms located in eastern regions. This study provides empirical evidence on the effectiveness of AI Pilot Zones in promoting green innovation among manufacturing firms and clarifies the underlying mechanisms. Full article

Global climate governance is undergoing a rapid transformation, and energy systems are increasingly shifting toward low-carbon development. Against this background, improving manufacturing firms’ green total factor productivity (MFGTFP) is essential for achieving sustainable industrial development. China has introduced two major policy instruments: new energy demonstration cities (NEDCs) and low-carbon city pilots (LCCPs). NEDCs focus on optimizing the energy supply structure, whereas LCCPs seek to reduce carbon emissions through demand-side regulatory constraints. This study treated the joint implementation of NEDCs and LCCPs as a quasi-natural experiment and employed panel data from Chinese A-share listed manufacturing firms from 2007 to 2024. Using a multi-period difference-in-differences model and mechanism tests, we examined the effect of the joint implementation of these policies on MFGTFP. The empirical results show that the joint implementation of NEDCs and LCCPs significantly improves MFGTFP. This effect is more pronounced when NEDCs are introduced prior to LCCPs, particularly in cities with a higher government ecological governance capacity (GEGC) and in regions characterized by a lower carbon emission intensity (CEI). Mechanism analysis revealed that the joint effects of NEDCs and LCCPs operate through supply-side innovation and partially through demand-side cost-pressure channels. On the supply side, NEDCs promote green innovation (GI), thereby enhancing firms’ supply innovation. On the demand side, the evidence mainly reflects financing constraint (FC) alleviation rather than a positive capacity utilization (CU) channel. Together, these findings suggest that improvements in MFGTFP are driven by supply-side innovation incentives and partially by demand-side cost-pressure effects through FC alleviation. These findings provide firm-level evidence on how the joint implementation of energy and carbon policies promotes green productivity improvement. Full article

As a core policy tool for promoting green economic transformation and high-quality development, green finance has significantly optimized the allocation of resources for corporate green innovation, thereby inevitably influencing the efficiency of green innovation in the manufacturing sector. Using the “Green Finance Policy Pilot Program” as a case study, this study employs a multi-period difference-in-differences (DID) model and robustness tests to examine the impact of green finance policies on the green innovation efficiency of Chinese manufacturing firms. The results indicate that green finance policies help enhance the green innovation efficiency of manufacturing firms. Mechanism analysis reveals that green finance policies enhance firms’ green innovation efficiency by alleviating financing constraints for green innovation, improving the quality of environmental information disclosure, and promoting collaborative green technology innovation. Heterogeneity results indicate that the positive correlation between green finance policies and firms’ green innovation efficiency is particularly pronounced among large-scale firms and firms in regions with high levels of green development. This study not only enriches the literature on the micro-level effects of green finance but also provides valuable insights for governments and firms seeking to enhance green innovation efficiency. Full article

This paper assesses the role of green hydrogen and green ammonia in the low-carbon reconstruction of Ukraine’s energy sector. The country, severely affected by war, has more than 70% of its energy infrastructure damaged or destroyed, which calls for novel solutions for not only reconstructing but also rethinking Ukraine’s energy sector shaped by the Soviet-era planning. In this context, decentralized and renewable energy solutions appear to be one of the best options to achieve this goal. This study combines four novel and mutually reinforcing methods: a Scopus-based literature review of highly cited green hydrogen publications, natural language processing (NLP) and bibliometric network analysis of Ukraine-related hydrogen research, a SWOT assessment, and a geospatial hydrogen production cost model (GEOH2). The novelty of this research lies in this integrated Ukraine-specific framework, which links research trends, wartime reconstruction constraints, hub-level policy choices, and financing risk-sensitive cost modeling. Therefore, the quantitative part of GEOH2 estimates the levelized cost of green hydrogen, while ammonia is treated as a downstream screening-level conversion and export pathway rather than as a full plant-level ammonia model. Our results show that Ukrainian green hydrogen research is concentrated on renewable-energy strategy, wind and solar electrolysis, water and desalination constraints, gas grid blending, underground storage, ammonia derivatives, and decentralized energy systems. The GEOH2 results indicate that southern Ukraine has strong physical potential for competitive green hydrogen production under de-risked financing, while war risk financing can make even resource-rich areas economically unattractive. Odesa and Dnipro emerge as important export-oriented and industrial hubs, whereas Zakarpattia remains strategically relevant as a safer western corridor linked to European markets. Our findings demonstrate that Ukraine’s hydrogen and ammonia development needs to follow a phased pathway: domestic renewable build-out and grid repair, pilot electrolysis projects and screening-level ammonia conversion pathways, targeted de-risking and insurance mechanisms, and only then broader export corridor development. This pathway can support decarbonization, energy security, industrial modernization, and Ukraine’s long-term integration into European clean energy value chains. Full article

In the context of extreme climate events and increasingly stringent environmental regulation, insufficient corporate green resilience has become a micro-level bottleneck to achieving China’s “dual-carbon” targets. Using panel data on Chinese A-share listed firms from 2015 to 2023, this study treats the approval of the National Pilot Zone for Artificial Intelligence Innovation Applications as a quasi-natural experiment and employs a double machine learning (DML)–augmented difference-in-differences framework to estimate the causal impact of the policy on firms’ green resilience. We find that the pilot-zone policy significantly increases corporate green resilience by about 32%, with stronger effects among high-tech firms, non-heavily polluting industries, regulated sectors, and large enterprises. Mechanism analyses show that the policy improves green resilience through four channels—accelerating green innovation, enhancing supply-chain efficiency, alleviating financing constraints, and reducing operating costs—with innovation and supply-chain efficiency playing dominant roles. These findings provide firm-level causal evidence that AI-oriented place-based policies can strengthen firms’ capability to sustain green development under disturbances and inform the coordination of the “Digital China” and “Dual Carbon” agendas. Full article

Building climate-resilient cities strengthens urban livability and sustainable development levels. This paper constructs a difference-in-differences model to examine the impact of the pilot policy for climate-resilient city construction (CRCC—CRCC is used uniformly in the following text to represent the policy) on green sustainable innovation, using panel data of 260 prefecture-level Chinese cities from 2009 to 2023. The results reveal that CRCC can significantly promote green sustainable innovation in Chinese cities. Additionally, CRCC promotes green sustainable innovation by increasing the level of informatization, improving green total-factor energy efficiency, boosting corporate ESG performance, and alleviating corporate financing constraints. Therefore, it is necessary to further strengthen the implementation and promotion of China’s climate pilot policy. Attention should be paid to optimizing the pathways through which the pilot policy affects green sustainable innovation. Differentiated regional policies should be implemented based on local conditions. A tripartite linkage mechanism involving the government, enterprises, and the public should be established to increase societal awareness and support for climate-resilient city construction. Full article

The deep integration of the digital economy and green finance is a key strategic arrangement for promoting high-quality industrial development in the new stage of development. This paper uses China’s dual pilot program—comprising both Big Data Comprehensive Pilot Zones and Green Finance Reform and Innovation Pilot Zones—as a quasi-natural experiment. Based on panel data from 285 prefecture-level cities spanning 2010–2023, and employing a dual machine learning approach, the study investigates how the digital economy and green finance synergistically enhance urban carbon total factor productivity. The study finds that, compared to cities with single-policy pilot programs, the synergy of digital and green policies can promote an increase in urban carbon total factor productivity. This conclusion remains valid after a series of robustness tests, including changing the sample period, adjusting machine learning model settings, and introducing instrumental variables. Mechanism tests indicate that the synergy of digital and green policies can enhance urban carbon total factor productivity through three pathways: increasing government focus on green development, raising the level of urban green technological innovation, and expanding the scale of green investment. Heterogeneity analysis reveals that the synergistic effects vary across cities with different resource endowments and geographical locations. This study uncovers the underlying logic of how the digital economy and green finance synergistically drive urban development and transformation, providing empirical evidence from China for the formulation of sustainable development policies tailored to local conditions. Full article

Green finance (GF) is increasingly seen as an important policy tool for promoting sustainable urban development; however, its role in facilitating the green transformation of urban land remains insufficiently understood, particularly from the perspectives of land use efficiency and spatial interactions. This study takes China’s Green Finance Reform and Innovation Pilot Zones as a quasi-natural experiment and employs a spatial difference-in-differences framework to examine whether and how GF affects urban land green use efficiency (LGUE). The results indicate that GF significantly improves LGUE in pilot cities, and this finding remains robust across a range of alternative specifications and robustness checks. The mechanism analysis further suggests that GF enhances LGUE primarily by optimizing resource allocation, promoting green innovation, and strengthening information disclosure. In addition, digital development is found to reinforce the positive effects of GF. Compared with existing studies, this paper integrates mechanism analysis with spatial econometric methods to provide a more comprehensive understanding of both the transmission channels and spatial spillover effects of GF. In particular, it provides new evidence on geographically constrained negative spillover effects across cities. The results further indicate that such spillover effects are most pronounced within a 250 km radius, suggesting that GF induces localized inter-city competition and resource reallocation. This finding offers empirical support for understanding the effects of GF from a spatial competition perspective. This study highlights the necessity of coordinating regional policy design to mitigate spatial spillover effects and improve the overall effectiveness of green finance policies. Full article

Under China’s dual-carbon goals, Green Finance Policy (GFP) and the Environmental Protection Tax Policy (ETP) are key tools for firm-level green transformation, yet their joint micro-effects remain underexplored. Using Shanghai and Shenzhen A-share listed firms from 2011–2022, this study treats the overlapping rollout of the Green Finance Reform and Innovation Pilot Zones and the Environmental Protection Tax reform as a staggered quasi-natural experiment and applies a multi-period DID to identify their synergistic effect on Corporate Green Technology Innovation. Results show that each policy alone promotes green innovation and that their coordination further strengthens the effect. The synergy operates mainly by easing financing constraints and increasing R&D investment. The effect is stronger among firms with better resources, governance, and digitalization, and in regions with stronger institutional environments; it is also more evident in non-heavy-polluting and non-manufacturing sectors. While the policy mix raises both innovation quantity and quality, it does not significantly improve total factor productivity, indicating a “weak Porter effect.” These findings provide micro-level evidence on GFP–ETP synergy and inform the refinement of green finance, environmental tax design, and firm-level green transition policies. Full article