Search Results (740)

When the Sustainable Development Plan for National Resource-Based Cities (SDPNRBC) incorporated tourism into its 2013 policy framework, cities of all sizes pursued tourism-led transitions. More than a decade on, this study asks whether these efforts have translated into genuine improvements in tourism efficiency. Using panel data from 258 Chinese prefecture-level cities spanning 2003 to 2023, we treat the SDPNRBC as a quasi-natural experiment and apply a difference-in-differences framework. Cities covered by the plan saw significant expansion in tourism scale, but tourism total factor productivity declined over the same period, indicating that growth was driven by factor accumulation rather than by genuine efficiency gains. Two channels appear to explain this divergence. The policy triggered a green paradox in which extractive firms accelerated output before tighter regulations took effect, undermining the environmental quality on which tourism depends. In parallel, policy-induced structural reallocation expanded labour-intensive service activity at a pace that outstripped complementary capital and skill formation, a pattern analogous to Baumol’s cost disease. A life-cycle heterogeneity analysis sharpens these findings: efficiency losses concentrate in Growing cities, attenuate in Mature cities, and disappear in Declining and Regenerating cities. Successor-industry policies should therefore be calibrated to where each city stands in its resource life cycle. Full article

Income inequality remains a central impediment to inclusive growth, yet whether government-led digital infrastructure programs mitigate or exacerbate distributional disparities is empirically contested. Exploiting the staggered rollout of China’s “Broadband China” (BBC) demonstration cities as a quasi-natural experiment, this study employs a multi-period difference-in-differences (DID) framework on a panel of 281 prefecture-level cities spanning 2009–2022 to estimate the designation effects of national digital infrastructure policy under the DID identifying assumptions. After parallel-trends validation, permutation-based placebo tests, and propensity score matching, the baseline estimates indicate a dual distributional pattern: BBC designation is associated with a wider urban-rural income gap and lower within-prefecture nighttime-light-based spatial income inequality. Candidate-channel analysis provides evidence consistent with financial deepening and factor mobility as plausible pathways: expanded financial coverage and cross-regional labor reallocation are associated with spatial convergence, whereas asymmetric usage depth and selective labor mobility reinforce urban-rural divergence. Exploratory heterogeneity analysis across four institutional dimensions, officials’ political promotion incentives, local fiscal capacity, traditional infrastructure endowments, and urban hierarchy, further shows that this distributional pattern varies across local contexts. Furthermore, this study extends the analytical lens to the spatial dimension by employing a spatial DID framework. The results identify significant cross-border externalities characterized by cross-prefecture spillovers associated with lower within-prefecture nighttime-light-based spatial income inequality in neighboring cities. These findings provide an integrated policy-evaluation framework that disentangles the complex, multidimensional distributional consequences of digital infrastructure investment, offering actionable insights for designing more equitable digital public policies in developing economies. Full article

Background/Objectives: Preoperative anxiety is common in adult patients undergoing oral and dentoalveolar surgical procedures under local anesthesia and may impair cooperation, physiological stability, and overall treatment experience. While intravenous sedation and general anesthesia provide effective anxiolysis, they increase anesthetic exposure and recovery demands. Targeted preoperative anxiolysis offers a less invasive strategy to reduce anxiety while preserving responsiveness. However, approaches vary and standardized protocols are lacking. This systematic review evaluated the efficacy and safety of preoperative anxiolytic interventions—including both pharmacological and non-pharmacological strategies—in adult patients undergoing oral surgical procedures under local anesthesia without general anesthesia or deep sedation. Methods: The review adhered to the PRISMA 2020 guidelines and was prospectively registered in PROSPERO (CRD420261281592). Randomized and quasi-randomized controlled trials published between 2016 and 2026 were identified through structured searches of PubMed/MEDLINE, ScienceDirect, and Springer Nature Link. Eligible studies included adult patients undergoing oral surgery under local anesthesia and evaluated preoperative anxiolysis using validated instruments such as the Dental Anxiety Scale (DAS), State–Trait Anxiety Inventory (STAI), and Visual Analog Scale for Anxiety (VAS-A). Risk of bias was assessed using the Cochrane RoB 2 tool. Owing to methodological heterogeneity, results were synthesized narratively. Results: Eight trials (n = 617) met the inclusion criteria. Interventions included oral benzodiazepines, melatonin, pregabalin, herbal agents, nitrous oxide, and auriculotherapy. Benzodiazepines consistently reduced anxiety scores (p < 0.05) without significant interagent differences. Pregabalin at a dose of 150 mg significantly lowered STAI-S and VAS-A scores (p < 0.001). Passiflora incarnata was comparable to midazolam and superior to placebo, whereas Erythrina mulungu showed no effect. Melatonin results were inconsistent. Hemodynamics remained stable, and adverse events were mild. Conclusions: Preoperative anxiolysis under local anesthesia effectively reduces anticipatory anxiety in oral surgery, with benzodiazepines demonstrating the most consistent efficacy. Further standardized trials are warranted. Full article

Land-use change is a major driver of climate change and carbon-cycle imbalance, yet its dual effects on carbon emissions and carbon sinks remain insufficiently examined in the context of rural spatial restructuring. As a key form of county-level rural land-use transformation in China, the Village Merger and Resettlement (VMR) policy reshapes the spatial distribution of rural population and land by concentrating residents, vacating idle homesteads, and optimizing land allocation. Treating VMR as a quasi-natural experiment, this study uses county-level panel data and a difference-in-differences approach to evaluate its impacts on regional carbon emissions and carbon-sink capacity. The findings indicate that VMR significantly reduces regional carbon emissions while enhancing carbon-sink capacity. Mechanism analysis shows that the emission-reduction effect operates mainly through population concentration, centralized infrastructure provision, and reduced household energy consumption, whereas the carbon-sink effect is driven by land intensification, agricultural mechanization, cultivated land-use adjustment, and improved vegetation cover. Heterogeneity analysis further reveals stronger emission-reduction effects in areas with a larger pre-policy urban–rural income gap and higher urbanization rates, and stronger carbon-sink effects in areas with greater terrain fragmentation and higher elevations. These findings suggest that rural spatial restructuring can contribute to regional carbon governance. Full article

This study examines how power transmission infrastructure expansion reshapes manufacturing agglomeration and regional industrial systems. Taking China’s ultra-high-voltage (UHV) transmission projects as a quasi-natural experiment, we investigate their impact on manufacturing agglomeration. Using panel data from 282 prefecture-level cities over the period 2006–2020, we adopt a comprehensive empirical strategy centered on a multi-period difference-in-differences (DID) framework, complemented by synthetic DID, propensity score matching, instrumental variable approaches, and double machine learning methods to ensure robust causal inference. The results show that UHV projects significantly promote manufacturing agglomeration, indicating a substantial reconfiguration of regional industrial systems. This effect operates through increased power supply in input areas, the release of resource advantages in output areas, and market scale expansion. Both input and output sides have significant positive effects, with a stronger impact from the input side. Moreover, government intervention and infrastructure development further amplify the agglomeration effect. Furthermore, the manufacturing agglomeration induced by UHV projects promotes economic growth, green development, and urban sustainability. These findings provide system-level insights into the role of power transmission infrastructure in energy–industrial integration and offer implications for the design and optimization of sustainable energy systems. Full article

In the context of rapid urbanization and climate change, evaluating urban forest development and the effectiveness of related policies is of great significance. This study takes Chinese prefecture-level cities as the research object and constructs an evaluation system for Urban Forest Development Effectiveness (UFDE), encompassing forest networks, forest health, ecological welfare, and development coordination. The analytic hierarchy process–entropy weight method is employed to measure UFDE. On this basis, leveraging the quasi-natural experiment formed by the staggered implementation of the National Forest City Policy (NFCP), this paper applies double machine learning (DML) to identify the causal effects of the policy. The results show that NFCP significantly improves UFDE, and this conclusion remains robust across various model specifications and robustness checks. Meanwhile, the policy effects exhibit significant heterogeneity, being more pronounced in eastern and central regions, as well as in humid climate zones, while being relatively weaker in western and arid regions. Methodologically, this study introduces DML to enhance the precision of causal identification, and in terms of measurement, it achieves a multidimensional, comprehensive evaluation. It provides a new analytical framework for assessing environmental policy effectiveness and offers empirical evidence for optimizing urban ecological governance and promoting green development. Full article

Environmental policies play an important role in promoting corporate green innovation, yet existing studies often treat such policies as a single exogenous shock and pay limited attention to the institutional context in which firms respond. Using the Low-Carbon City Pilot (LCCP) policy in China as a quasi-natural experiment, this study examines how environmental policies influence corporate green innovation. Based on panel data of Chinese A-share listed firms from 2007 to 2023, a staggered difference-in-differences model is employed to identify the policy effect. The results show that the LCCP policy significantly promotes corporate green innovation and stimulates both substantive and strategic green innovation. From the perspective of institutional logics, capital market time orientation plays an important moderating role: long-term institutional investors strengthen the positive policy effect, while short-term institutional investors weaken it. Mechanism tests further show that the policy promotes green innovation mainly by increasing managerial attention to environmental and low-carbon issues, while its effect on temporal attention allocation is not significant. These findings highlight the importance of institutional contexts and managerial attention in shaping firms’ strategic responses to environmental policies and provide new empirical evidence on how environmental governance policies influence corporate green innovation. 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

As a strategic infrastructure supporting high-quality economic and social development, computing infrastructure plays a pivotal role in enabling green transitions. Using panel data from Chinese prefecture-level cities spanning 2007 to 2023 and leveraging the staggered commissioning of 12 National Supercomputing Centers as a quasi-natural experiment, this paper employs a time-varying difference-in-differences (DID) approach to estimate the effect of computing infrastructure on urban green total factor productivity (GTFP). The results indicate that the operation of supercomputing centers has a statistically significant positive effect on urban GTFP, with a magnitude equivalent to approximately 0.83 times the sample standard deviation of GTFP, a finding that remains robust to alternative dependent variable specifications, the exclusion of other policy shocks, and placebo tests. Mechanism analysis reveals that computing infrastructure facilitates green development through three channels: fostering green technological innovation, optimizing energy efficiency, and strengthening environmental regulation. Heterogeneity analysis shows that the positive effect is more pronounced in coastal cities, small-to-medium-sized cities, and regions with weaker digital infrastructure. Spatial analysis further uncovers a distance-decay pattern, with a siphoning effect within a 50 km radius and a spillover effect between 50 km and 200 km from the supercomputing center. This study provides empirical evidence on the environmental consequences of the computing economy and offers policy implications for optimizing computing infrastructure deployment to facilitate green transitions. Full article

In the context of global climate change and industrial low-carbon transition, whether environmental taxes can simultaneously promote environmental and economic benefits by stimulating corporate green investment remains a central issue in academic research. Existing studies have reached mixed conclusions regarding the effects of environmental taxes, emphasizing either the “innovation compensation” effect or the “crowding-out” effect. However, this binary perspective overlooks the internal boundary conditions under which environmental taxes operate, particularly the roles of market competition and firm-level resource endowments. In particular, limited attention has been paid to how competitive market environments shape firms’ responses to environmental regulation. To address this gap, this study develops an integrated analytical framework that combines external market competition with internal firm endowments. Using China’s 2018 Environmental Protection Tax Law as a quasi-natural experiment and a panel dataset of Chinese listed firms from 2009 to 2024, this study employs a Difference-in-Differences (DID) approach to examine the impact of environmental taxation on corporate green investment. The results show that: (1) the environmental protection tax significantly promotes corporate green investment, with substantial heterogeneity across firm size, ownership structure, and regional institutional environments; (2) market competition serves as an important external moderating mechanism, as intensified competition strengthens firms’ incentives to pursue technological differentiation through green investment, thereby generating an “escape-competition effect”; and (3) from an internal perspective, the effectiveness of environmental taxation is also shaped by firm endowments. High investment activity provides the necessary resource buffer to support strategic pivots, whereas rapid revenue growth and high financial slack (excessive cash ratio) generate strategic inertia, thereby attenuating firms’ responsiveness to the tax shock. This study not only provides empirical evidence from China on the mechanisms through which environmental taxes influence corporate green transformation, but also offers important policy implications for improving environmental tax systems in other countries. Full article

Sino–U.S. trade friction (SUTF) has imposed significant shocks on economic systems and firm operations, attracting growing scholarly attention. This study investigates the impact of SUTF on corporate innovation quality and its underlying mechanism. Using the U.S. Section 301 investigation as a quasi-natural experiment, we adopt a difference-in-differences (DID) research design. The results indicate that SUTF significantly enhances corporate innovation quality, and this positive effect is partially mediated by the adoption of artificial intelligence (AI)—a general-purpose technology that reshapes traditional organizational and management systems. Moreover, the innovation-enhancing effect of SUTF is more pronounced among firms with a higher proportion of executives with IT experience and those with stronger corporate governance. These findings contribute to the literature on the economic consequences of SUTF by revealing AI adoption as a novel mechanism. This study also offers practical insights for firms navigating an era of heightened trade tensions and can inform policies aimed at fostering high-quality innovation. Full article

The digital economy has changed the way agricultural production is organized and how rural households access markets, jobs, and information. Yet it remains unclear whether these changes translate into higher income for rural residents, especially in major agricultural regions. This study examines the income effect of digital infrastructure development by using the rollout of the Broadband China policy as a quasi-natural experiment. The analysis draws on panel data for 77 prefecture-level administrative units in the Yellow River Basin, one of China’s major agricultural regions, from 2009 to 2021. A staggered difference in differences model is used to estimate the policy effect. The results show that digital infrastructure development significantly increases rural residents’ income. Under the log income specification, the baseline coefficient indicates an average income increase of about 8.33%. The mechanism analysis shows that innovation capacity and nonfarm employment both serve as positive partial transmission channels, with innovation capacity explaining a larger share of the total effect. The heterogeneity results suggest that the income effect is stronger in regions with higher GDP and larger population size. These findings indicate that digital infrastructure can support rural income growth when it is linked with local innovation capacity, employment opportunities outside agriculture, and rural development policies suited to local conditions. Full article

Against the backdrop of China’s “dual carbon” goals and urban green transition, improving urban land use efficiency is essential for shifting land development from extensive expansion to intensive and low-carbon use. Using the Low-Carbon City Pilot Program as a quasi-natural experiment, this study examines panel data from 285 prefecture-level cities in China from 2007 to 2023. We apply a multi-period difference-in-differences model, a threshold regression model, and a spatial Durbin model to assess the program’s impact on urban land use efficiency. The results show that the pilot program significantly improves urban land use efficiency, and the effect persists over time. This finding remains robust across a series of robustness checks. Heterogeneity analysis shows that the efficiency gains are stronger in cities with lower air pollution control pressure, higher industrial pollution control pressure, and lower fiscal pressure. Further threshold analysis shows that digital connectivity is a key condition for strengthening the policy effect. The spatial analysis suggests that the policy effect shows some spatial association. However, the decomposed indirect and total effects are not robust, so the spatial results should be interpreted with caution. This study provides empirical evidence on how low-carbon city pilots affect urban land governance and land use efficiency. Its conclusions, however, remain subject to limitations related to efficiency measurement, policy identification, and the availability of city-level data. Full article

Rural e-commerce is reshaping agricultural markets, yet its environmental consequences remain insufficiently understood. This study examines how the Rural E-commerce Comprehensive Demonstration (RECD) program affects agricultural carbon outcomes in China. Using a balanced panel of 2152 counties from 2010 to 2022, we employ a multi-period difference-in-differences (DID) model to identify the effect of the RECD policy. The results show that the RECD policy significantly increases total agricultural carbon emissions. Evidence for production expansion and production restructuring suggests that improved market access and stronger price incentives encourage output expansion and a shift toward more market-oriented production, thereby raising aggregate emissions. At the same time, the RECD policy significantly reduces the carbon emission intensity and improves the carbon emission efficiency, indicating better carbon performance per unit of agricultural output. Further analysis shows that this dual result reflects the coexistence of efficiency gains and scale expansion, with the scale effect dominating the technical effect at the current stage. The emission-increasing effect is more pronounced in balanced agricultural areas, poverty-designated counties, counties with weaker initial e-commerce foundations, and counties with higher initial emission levels, while stronger environmental regulation and green technological innovation significantly mitigate this effect. In addition, the RECD policy generates spillover effects on neighboring counties within 50 km. These findings provide empirical evidence on the effects of the RECD policy on agricultural carbon emissions and offer policy guidance for integrating rural e-commerce policies with low-carbon agricultural transformation. Full article

This study examines whether stricter enforcement of mandatory social insurance contributions affects corporate income tax behavior in China. In the Chinese institutional context, mandatory social insurance refers to payroll-based employer and employee contributions to five statutory programs: basic pension insurance, basic medical insurance, work-injury insurance, unemployment insurance, and maternity insurance. These programs are directly related to social sustainability because they finance old-age income security, medical protection, workplace injury compensation, unemployment support, maternity protection, and labor-market stability. Using China’s 2018 social insurance collection reform as a quasi-natural experiment, we analyze A-share listed companies from 2014 to 2024 through a difference-in-differences design based on differential exposure between private firms and state-owned enterprises. To assess the reliability of the identification strategy, we employ firm and year fixed effects, event-study analysis, placebo tests, alternative measures of tax avoidance, and propensity score matching difference-in-differences robustness checks. The findings show a tax-fee seesaw effect: private firms subject to extensive regulatory scrutiny respond to more rigorous enforcement of social insurance contributions by increasing corporate income tax avoidance. Analysis of the mechanisms shows that the Whited-Wu index of financial constraints partially explains this phenomenon. The effect is more pronounced in firms with higher labor costs and greater administrative expense intensity, indicating that the increased response is driven by labor cost exposure and organizational discretion. By contrast, the effect is weaker among firms audited by the Big Four accounting networks—Deloitte, PricewaterhouseCoopers, Ernst & Young, and KPMG—indicating that high-quality external audits constrain aggressive tax planning. Regionally, the effect is most pronounced in eastern China, where markets, labor costs, and tax-planning services are more developed. The findings contribute to the sustainable development literature by demonstrating that reforms designed to strengthen social insurance sustainability can unintentionally weaken tax compliance if payroll contributions, tax administration, and corporate financial pressures are not coordinated. The study highlights the importance of integrated fiscal governance for achieving socially sustainable and fiscally balanced development. Full article