Search Results (793)

In schools located in the Colombian Amazon, there is still limited empirical evidence on how students connect pro-environmental values with emotions and environmental peace culture. In this article, environmental peace culture is understood as a way of learning to care for nature, live with it, and assume shared responsibility for its protection. The study investigated “Sembrando Paz Ambiental”, a place-based pedagogical proposal implemented among secondary school students through experiential, playful, and participatory activities. A convergent mixed-methods design was employed, integrating a quasi-experimental pretest–posttest component with a qualitative analysis of students’ perceptions and pedagogical productions. The quantitative component included 66 paired cases assessed through a 24-item Likert scale, with data analyzed using the Wilcoxon signed-rank test. The qualitative component included open-ended responses, drawings, and written productions analyzed through thematic coding and co-occurrence analysis in ATLAS.ti. The findings revealed statistically significant increases across all pro-environmental values, with the hedonic value showing the largest effect size. Qualitative findings associated environmental peace culture with emotional well-being, cooperation, care for nature, and territorial belonging. The study contributes to the literature by showing that the mobilization of pro-environmental values depends not only on normative conservation discourses, but also on pedagogical experiences that connect emotion, territory, and environmental care. Full article

The reconfiguration of global value chains has raised concerns about the resilience and upgrading of manufacturing supply chains. This study examines whether digital infrastructure improves manufacturing supply chain capabilities, using the 2016 “Information for the People” pilot city program as a quasi-natural experiment. Based on panel data from Chinese prefecture-level cities from 2006 to 2023, a difference-in-differences model is employed to identify the causal effect. The results show that digital infrastructure significantly enhances manufacturing supply chain capabilities, and this finding remains robust after multiple tests. Heterogeneity analysis indicates that the effect differs across China’s eight economic regions and strengthens with longer policy implementation, showing regional and cumulative characteristics. Mechanism analysis suggests that innovation-oriented talent inflow is an important transmission channel. Further analysis shows that financial development positively moderates the impact of digital infrastructure by improving cities’ capacity to absorb and allocate digital and innovation resources. These findings suggest that policymakers should shift from uniform digital infrastructure investment to region-specific strategies that integrate talent attraction, financial support, and supply chain modernization. Full article

Consumption is a basic driver of economic growth and a key part of the new development paradigm centered on the dual circulation of domestic and international markets. Treating the establishment of National E-Commerce Demonstration Cities as a quasi-natural experiment, this paper employs a multi-period difference-in-differences (DID) model and draws on panel data from Chinese prefecture-level cities spanning 2009 to 2023 to estimate the impact of the demonstration city policy on residents’ consumption levels and its transmission mechanisms. The findings are as follows: First, the National E-Commerce Demonstration City Policy significantly promotes residents’ consumption. Compared with the control group, consumption levels in demonstration cities increased by approximately 6.6%, and this result is robust to various specification checks. Second, mechanism analysis shows that the policy boosts consumption through three channels: stimulating urban entrepreneurship, upgrading smart logistics, and improving digital infrastructure. These channels together help build a more efficient consumption system. Third, heterogeneity analysis indicates that the policy effect is stronger in large cities, central and western regions, non-old industrial base cities, and cities with higher urbanization rates. These findings provide theoretical insights and practical implications for refining the e-commerce demonstration policy, tailoring it to local conditions, and unlocking consumption potential. Full article

Against accelerating urban expansion, climate risks, and green transition, fortifying urban ecological resilience (UER) has become central to global urban sustainability. However, there is as yet no systematic evidence to suggest how the National Innovative City Pilot Policy (NICPP) promotes green technology innovation (GTI) and strengthens UER. To address this gap, this paper builds upon the traditional resistance–adaptability–resilience (RAR) paradigm and its extension, the driving force–resistance–adaptability–resilience (DRAR) framework to formulate a comprehensive driving force–pressure–resistance–adaptability–resilience (DPRAR) assessment system. Moreover, this paper investigates a dataset of 271 cities in China spanning the period from 2006 to 2023. By treating the NICPP as a quasi-natural experiment, this paper integrates an entropy balancing technique into a staggered difference–in–differences (DID) model to identify its effect on UER. The results are outlined below. (1) From 2006 to 2023, UER across Chinese municipalities generally increased, though spatial imbalances persisted. (2) The NICPP enhanced urban UER, with effects characterized by time-lagged and cumulative patterns. (3) Both the quantity and quality structure of urban GTI served as channels through which the NICPP affected UER. (4) The NICPP effects are strongest in the central region, followed by those in the western and eastern regions, as well as in resource-dependent cities and cities with stricter environmental regulation. This research provides novel empirical perspectives linking innovation-driven development, GTI, and UER, with implications for NICPP optimization and UER enhancement in China. Full article

With the acceleration of global economic integration and the continuous rise of external uncertainties, the resilience and security of industrial and supply chains have become core benchmarks for measuring an economy’s risk resistance and sustainable development capacity, which is crucial to the stable operation of the modern economic system. Based on panel data covering 279 prefecture-level and above cities in China from 2003 to 2023, this paper takes the Pilot Program for Integrating Science, Technology and Finance as a quasi-natural experiment, and adopts a multi-period DID model to empirically examine the correlation between sci-tech finance policies and urban industrial chain resilience, as well as explore its potential transmission pathways. The results show that the pilot policy significantly improves urban industrial chain resilience. Financial deepening level, high-tech application level, and urban informatization level may serve as potential transmission channels through which the policy functions. Further heterogeneity analysis indicates that the policy effect varies markedly across cities in terms of location, scale, urban resource endowments, and industrial foundation. This study enriches relevant research on sci-tech finance policy effects and industrial chain resilience and provides theoretical basis and practical reference for optimizing sci-tech finance system design and consolidating industrial chain security. Full article

Building green data centers is an important task in constructing a new generation of information infrastructure and is an inevitable choice for promoting sustainable economic development. This study regards the implementation of the national green data center (NGDC) policy in batches as a quasi-natural experiment and uses the multiperiod difference-in-difference (DID) method to study the effect and mechanism of NGDC policy on the green transformation (GT) of Chinese listed enterprises. Research has found that the NGDC policy has a substantial improvement effect on the level of GT of enterprises, mainly achieved through two paths: enhancing the investment in environmental protection and improving the environmental, social, and corporate governance performance of enterprises. Heterogeneity analysis found that the effect of NGDC policy on empowering enterprises to improve their GT level is more remarkable in state-owned enterprises and those located in more competitive industries. In addition, the technology business environment and environmental regulation in the region emphasize the positive regulatory effect of NGDC policy on promoting enterprise GT. The results of this paper provide empirical evidence and policy implications for improving the construction of national green data centers and promoting sustainable development of enterprises. Full article

The systemic shift in the energy consumption structure from high-carbon fossil fuels to low-carbon clean energy constitutes a critical pathway toward global climate governance and carbon neutrality. However, this sustainable transition is consistently impeded by deep-seated institutional frictions and structural barriers, such as governance fragmentation and carbon lock-in effects embedded in traditional industrial organization. Whether digital government development can overcome these barriers by nurturing resilient business ecosystems and thereby promote a systemic low-carbon energy transition remains an urgent question within sustainable development research. To address this issue, this study integrates digital government development, regional e-commerce ecosystem competitiveness, and the low-carbon transition of the energy consumption structure into a unified analytical and sustainable governance framework. Using panel data from 30 Chinese provinces from 2012 to 2022, we exploit the institutional reform of provincial big data administrations as a quasi-natural experiment to identify the impacts of digital government. Regional e-commerce ecosystem competitiveness is comprehensively evaluated across four sustainable dimensions: ecological innovation capacity, market connectivity, ecological global integration, and inclusive infrastructure. Methodologically, we employ a spatial difference-in-differences model to capture geographic interdependencies alongside a double machine learning framework to handle high-dimensional confounding and nonlinear disturbances. The empirical findings reveal that both digital government development and regional e-commerce ecosystem competitiveness significantly drive the low-carbon transition of the energy consumption structure. The institutional effect of digital government exhibits strong regional embeddedness with localized impacts, whereas e-commerce ecosystem competitiveness generates positive spatial spillovers that accelerate energy optimization in neighboring regions. Crucially, regional e-commerce ecosystem competitiveness serves as a significant partial mediator, constructing a reliable transmission channel from institutional design to market-based decarbonization. Further pathway analysis indicates that market connectivity and inclusive infrastructure function as the primary transmission channels, effectively mitigating transportation energy intensity and bridging the digital-green divide, while the mediating contribution of ecological innovation capacity is relatively constrained due to cross-organizational coordination thresholds. This study clarifies the interactive mechanism between public digital governance and market ecosystem competitiveness in advancing environmental sustainability, thereby offering fresh theoretical insights and actionable policy implications for emerging market economies striving for economic growth and decarbonization. Full article

Facing the energy use rights trading system with an emphasis on source control, will enterprises opt for traditional fossil energy technology innovation or new and renewable energy technology innovation, and will they choose substantive or strategic innovation activities? Will the energy use rights trading system lead to competitive crowding-out effects or innovation compensation effects for corporate energy technology innovation? Taking the “Pilot Program for the Paid Use and Trading of Energy-Consumption Rights” as a quasi-natural experiment, this paper, based on the energy technology patent data of listed companies, conducts a theoretical analysis and a series of empirical tests to examine the impact of the energy use rights trading system on corporate energy technology innovation. The results indicate the following: Firstly, the energy use rights trading system significantly enhances corporate energy technology innovation, primarily inducing traditional fossil energy conservation innovations, while the driving effect on new and renewable energy technology innovation is not pronounced. Secondly, the system promotes corporate energy technology innovation by strengthening financing channels such as government subsidies. Thirdly, the energy technology innovation induced by this system stems from the competitive crowding-out effect on R&D resources, rather than the innovation compensation effect. Fourthly, the driving effect of the tradable energy permit system exhibits distinct path-dependent characteristics, which is manifested in the fact that the system exerts a more significant driving effect on substantive energy technology innovation activities, the most prominent impact being on substantive innovation in traditional fossil energy. Finally, enterprises across pilot regions respond differently to the system, with Zhejiang and Fujian Provinces showing more significant driving effects in energy technology innovation. The system mainly stimulates substantive innovation activities in non-state-owned, large-scale, and low-energy-consuming enterprises. This study contributes to the refinement of the energy use rights trading system and supports innovation-driven energy transition. Full article

Against the dual backdrop of the global green transition and China’s construction of a unified national market, the impact of environmental policies on the spatial allocation of capital has emerged as a core concern for academic researchers and policymakers alike. China’s implementation of the Environmental Protection Tax Law in 2018 completed the historic transition from the long-standing pollution discharge fee system to a formal environmental tax regime. While differentiated interprovincial tax rates under the new regime have the potential to reshape cross-regional capital flow patterns, existing literature lacks systematic micro-level empirical evidence regarding how environmental tax reform affects firms’ cross-regional investment and the underlying mechanisms driving such effects. This study constructs a sample of Chinese A-share-listed firms covering the period 2012 to 2024 and applies the difference-in-differences (DID) method to systematically examine the causal impact, transmission channels, and heterogeneous boundary conditions of environmental tax reform on firms’ cross-regional investment. The baseline estimation results confirm that environmental tax reform significantly stimulates cross-regional investment activities among firms located in provinces that raised environmental tax rates after the reform. This core conclusion remains robust across a series of validity checks, including parallel trend assumption tests, placebo tests, propensity score matching combined with difference-in-differences (PSM-DID) estimation, and the exclusion of confounding effects from contemporaneous policy interventions. Mechanism analysis identifies two core transmission channels through which the reform exerts its effects: rising pollution abatement costs and alleviation of corporate financing constraints. Further heterogeneity tests reveal that the promoting effect of the reform on cross-regional investment is more prominent for capital-intensive firms and firms located in regions with lower fiscal pressure and firms operating in regions with stricter environmental law enforcement. This study provides new micro-level empirical evidence supporting the applicability of both the pollution haven hypothesis and the Porter hypothesis in the Chinese institutional context and offers actionable policy insights for optimizing the design of the environmental tax system, guiding corporate green transformation, and facilitating coordinated regional development. Full article

In the era of carbon neutrality, urban competition has evolved from single-dimensional economic rivalry to multidimensional competition emphasizing green and sustainable development. However, it remains unclear whether digital infrastructure, the physical backbone of the digital economy, can externally enhance urban green competitiveness. Building on the measurement of urban green competitiveness through the super-efficiency SBM model, this study employs the “Broadband China” policy as an exogenous shock and uses a Staggered difference-in-differences (SDID) model to systematically analyze the impact and mechanisms of digital infrastructure on urban green competitiveness. The SDID model is adopted in this study for the following reason: the Broadband China strategy constitutes a phased rollout policy shock. By treating this policy as a quasi-natural experiment, the SDID framework enables more accurate identification of its causal impact on urban green competitiveness. The results show that the construction of digital infrastructure significantly promotes urban green competitiveness. Further analysis reveals that digital infrastructure enhances green competitiveness primarily through green technological innovation, industrial upgrading, and economic agglomeration, with the effect of economic agglomeration being stronger than that of the other two channels. Heterogeneity analysis shows that moderate government intervention amplifies the green effects of digital infrastructure. Moreover, the direct effect of digital infrastructure on green competitiveness is more significant in western cities than in eastern and central cities. This study provides empirical evidence for optimizing digital infrastructure development and achieving a “dual drive” of digitalization and green transformation. Full article

Sparse ergodic control provides a natural framework for long-run stochastic decision-making under resource constraints. Existing formulations, however, are typically restricted to control-affine systems with control-independent diffusion. When the diffusion coefficient depends explicitly on the control input, the associated ergodic Hamilton–Jacobi–Bellman (HJB) equation becomes non-separable through the term $\mathrm{t}\mathrm{r}\left[a\left(x, u\right){\nabla }^{2}V\right]$, so classical arguments based on control-affine separability no longer apply directly. In this work, we study sparse ergodic control of stochastic systems with control-dependent diffusion and nonlinear dynamics within a viscosity-solution and learning-based framework. To address the discontinuous ${\mathsf{\ell }}_0$-type sparsity penalty, we introduce smooth non-convex sparsity approximations that preserve differentiability while retaining sparse threshold behavior. Within a viscosity-solution framework, we analyze the existence and uniqueness properties of the associated ergodic pair and establish localized approximation error estimates for the smooth approximation. We further characterize a quasi-threshold sparse structure of the resulting optimal feedback policies in non-affine stochastic systems with control-dependent noise. On the computational side, we develop a Physics-Informed Neural Network (PINN)-based solver with adaptive residual-driven sampling for high-dimensional sparse ergodic HJB equations, together with a distributed monotone-inspired iterative scheme for weakly coupled multi-agent systems. Numerical experiments on multi-robot swarm navigation and renewable-integrated smart-grid control demonstrate that the proposed methods produce sparse control policies while preserving stable long-run performance under stochastic disturbances. Full article

The digitalization of tax administration (DTA) represents a transformative institutional reform; however, its influence on regional entrepreneurship remains both theoretically ambiguous and empirically understudied. Drawing on institutional theory, we examine whether and how DTA is associated with regional entrepreneurial entry by reshaping entrepreneurial resource allocation. Using China’s “Golden Tax Project III” reform as a quasi-natural experiment, we apply a staggered difference-in-differences approach to a panel of 282 cities from 2009 to 2022. The results show that the implementation of GTP III is associated with higher levels of entrepreneurial entry. Mechanism analyses provide evidence consistent with two primary channels: the agglomeration of technological talent and improved access to financial resources. Furthermore, the enabling effects of DTA are more pronounced in regions with more developed digital infrastructure, stronger administrative capacity, and higher institutional quality. These findings extend the literature by linking tax digitalization to regional entrepreneurial entry and by clarifying the mechanisms and boundary conditions under which its effects vary. Full article

The fundamental dilemma of energy transition lies in whether an economy can guide its energy system to break free from deep dependence on fossil fuels in a sustained and orderly manner. This requires not only institutional incentives for innovation but also, more critically, a social-level shift in focus from “physical expansion” to “human development.” This paper incorporates these two conditions into a unified causal framework. Taking the pilot program for the construction of IP-strong provinces in China launched in 2016 as a quasi-natural experiment, and using panel data from 30 provincial-level administrative regions in China over the period 2010–2022, this study employs the Spatial Durbin Difference-in-Differences (SDM-DID) model and the Double Machine Learning (DML) method to examine the joint impacts and transmission mechanisms of the regional IP strong chain and the deep synergy between investment in physical capital and investment in human capital on energy green controllability. The findings are as follows. First, both the IP strong chain and deep synergy significantly improve energy green controllability. The local effect of deep synergy is far greater than the direct effect of the IP system itself, making it the core structural force driving the green transition. Second, the institutional dividend of the IP strong chain generates positive spatial spillovers to neighboring regions through the patent information disclosure channel. In contrast, the spatial spillovers of deep synergy are obstructed by administrative barriers and fiscal boundaries. Third, deep synergy plays a significant partial mediating role in the process through which the IP strong chain affects energy green controllability, with more than one-third of the total policy effect being released through this channel. Fourth, a path-wise test reveals a notable structural difference: the human capital investment path significantly outperforms the physical capital investment path in terms of transmission efficiency and robustness. This indicates that, at the current stage, the institutional effectiveness of the IP system in driving the green transition is largely achieved by improving the quality, capacity, and security level of human capital, rather than by restructuring the physical capital stock. The above conclusions remain robust after replacing the machine learning algorithm, adjusting the sample split ratio, and excluding the interference of concurrent competitive policies. This paper reveals the complete causal chain through which institutional public goods are transmitted to system governance capacity via the factor allocation structure, providing new empirical evidence for understanding the deep-seated relationship between intellectual property governance and the energy transition. Full article

The manufacturing sector’s significant contribution to global carbon emissions necessitates effective decarbonization. This study evaluates the causal effect of exposure to China’s “Made in China 2025” (MIC) initiative, an industrial policy promoting intelligent manufacturing, on firms’ estimated carbon emissions by exploiting the policy as a quasi-natural experiment. Employing a Difference-in-Differences (DID) model on a panel of Chinese A-share manufacturing firms from 2011 to 2022, we find that exposure to the MIC policy is associated with an approximately 0.5% reduction in firms’ estimated carbon emissions. Although the reduction appears modest at the firm level, its aggregate effect may be substantial given the large scale of China’s manufacturing sector. Various robustness checks confirm the validity and persistence of this effect. Crucially, the environmental benefits are heterogeneous, showing stronger effects in competitive, technology-intensive, and labor-intensive sectors compared to capital-intensive ones. Mechanism analysis reveals that exposure to the MIC policy promotes substantive green innovation, accelerates digital transition through process optimization, and significantly enhances energy efficiency, thereby contributing to lower estimated firm-level carbon emissions. These findings underscore the potential role of intelligent-manufacturing-oriented industrial policies in reconciling industrial growth with climate mitigation and provide micro-level evidence on the environmental effects of policy-induced intelligent manufacturing transformation, extending a literature that has largely focused on economic outcomes. The results also suggest that policymakers should further promote intelligent manufacturing and design sector-specific green technology support policies, particularly for capital-intensive sectors where carbon-reduction effects appear relatively weaker, to maximize carbon reduction benefits. 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