China’s Climate Policy:Mandate-Based vs.Market-Based Approaches

Mandate-based and market-based mechanisms represent two primary approaches to achieving policy objectives,yet the debate over their relative effectiveness remains unresolved.The mandate-based approach is exemplified by pilot programs for low-carbon provinces and cities,referred to as“Low-Carbon Pilot Provinces/Cities”,while the market-based mechanism is reflected in pilot programs for carbon emissions trading markets,or“Carbon Trading Pilot Programs”.This paper employs event study analysis to compare the carbon emission reduction impacts of these two approaches.Our findings reveal that the Low-Carbon Pilot Provinces/Cities achieved emissions reduction primarily by curbing economic output,without significantly reducing carbon emissions intensity.In contrast,the Carbon Trading Pilot Programs led to an increase in total carbon emissions by driving economic growth,even as they reduced carbon emissions intensity.A heterogeneity analysis further indicates that the emissions reductions observed in the Low-Carbon Pilot Provinces/Cities were predominantly concentrated in economically less-developed regions,whereas the increase in carbon emissions associated with the Carbon Trading Pilot Programs was more significant in regions with lower initial carbon emissions intensity.Against the backdrop of China’s efforts to achieve its carbon peak and neutrality goals,this paper offers valuable insights for the design of effective climate policies.

Digital Economy and Corporate Innovation-Washing--An Empirical Study on How Information Mitigates Policy Distortion

As stated in the Report to the 20th National Congress of the Communist Party of China(CPC),innovation remains at the heart of China’s modernization drive,and it is vital to optimize the allocation of innovation resources,deepen structural scientific and technological reforms,and enhance the overall performance of China’s innovation system.Government incentives have boosted firm R&D and innovation efforts;however,they have also triggered an innovation dilemma where enterprises,capitalizing on their informational advantages,resort to innovation-washing behaviors that undermine the intended purpose of the policies.Based on the information asymmetry theory,this paper conducts an empirical study on how the digital economy affects firms’innovation-washing behavior.The development of the regional digital economy could suppress firm innovation-washing behavior in the region,and such a mitigation effect is primarily caused by an increase in the number of digital industry professionals.According to our heterogeneity analysis,the digital economy has a greater impact on firm innovation-washing behavior for certain types of enterprises,including non-state-owned enterprises(non-SOEs),small and medium-sized enterprises(SMEs),enterprises in less competitive industries,and enterprises in unfavorable business environments.Our mechanism analysis revealed that the digital economy may restrain innovation-washing behavior by reducing information asymmetry between enterprises and external stakeholders.In terms of economic outcomes,the digital economy has the potential to directly influence firm innovation output while also indirectly mitigating the subsequent decline in innovation output by discouraging innovation-washing.This paper enriches the research findings on how the digital economy breaks down“information silos”and offers a potential solution to the“emphasis on input and quantity over quality and efficiency”phenomenon in science and technology innovation practices.

Deep reinforcement learning based integrated evasion and impact hierarchical intelligent policy of exo-atmospheric vehicles

Exo-atmospheric vehicles are constrained by limited maneuverability,which leads to the contradiction between evasive maneuver and precision strike.To address the problem of Integrated Evasion and Impact(IEI)decision under multi-constraint conditions,a hierarchical intelligent decision-making method based on Deep Reinforcement Learning(DRL)was proposed.First,an intelligent decision-making framework of“DRL evasion decision”+“impact prediction guidance decision”was established:it takes the impact point deviation correction ability as the constraint and the maximum miss distance as the objective,and effectively solves the problem of poor decisionmaking effect caused by the large IEI decision space.Second,to solve the sparse reward problem faced by evasion decision-making,a hierarchical decision-making method consisting of maneuver timing decision and maneuver duration decision was proposed,and the corresponding Markov Decision Process(MDP)was designed.A detailed simulation experiment was designed to analyze the advantages and computational complexity of the proposed method.Simulation results show that the proposed model has good performance and low computational resource requirement.The minimum miss distance is 21.3 m under the condition of guaranteeing the impact point accuracy,and the single decision-making time is 4.086 ms on an STM32F407 single-chip microcomputer,which has engineering application value.

Timely Policy Exit:Reducing Over-Investment and Driving High-Quality Firm Performance

Using data from the 11th to 14th Five-Year Plan periods(2006-2025),this study applies a Difference-in-Differences(DID)approach to assess the impact of industrial policy withdrawal.Industries that have faced policy withdrawal for over a decade are categorized as the treatment group,while consistently supported industries form the control group.The analysis examines how withdrawal affects firm total factor productivity(TFP)and investment behavior.The results show that policy withdrawal boosts firm TFP by reducing over-investment and improving the efficiency of R&D spending.This effect is particularly evident in industries with strong,competitive leading firms.Additionally,in regions with lower levels of marketization,timely policy withdrawal plays a key role in curbing over-investment.This study also highlights a dual effect of policy withdrawal:while it fosters corporate social responsibility,it may also encourage financial speculation.These findings suggest that the implementation of industrial policy should provide“timely assistance”over a limited timeframe rather than long-term support to well-established industries.As industries mature,policy support should be gradually reduced or phased out to avoid over-investment and enhance firm efficiency.

A quantitative study of disruptive technology policy texts:An example of China’s artificial intelligence policy

Purpose:The transformative impact of disruptive technologies on the restructuring of the times has attracted widespread global attention.This study aims to analyze the characteristics and shortcomings of China’s artificial intelligence(AI)disruptive technology policy,and to put forward suggestions for optimizing China’s AI disruptive technology policy.Design/methodology/approach:Develop a three-dimensional analytical framework for“policy tools-policy actors-policy themes”and apply policy tools,social network analysis,and LDA topic model to conduct a comprehensive analysis of the utilization of policy tools,cooperative relationships among policy actors,and the trends in policy theme settings within China’s innovative AI technology policy.Findings:We find that the collaborative relationship among the policy actors of AI disruptive technology in China is insufficiently close.Marginal subjects exhibit low participation in the cooperation network and overly rely on central subjects,forming a“center-periphery”network structure.Policy tool usage is predominantly focused on supply and environmental types,with a severe inadequacy in demand-side policy tool utilization.Policy themes are diverse,encompassing topics such as“Intelligent Services”“Talent Cultivation”“Information Security”and“Technological Innovation”,which will remain focal points.Under the themes of“Intelligent Services”and“Intelligent Governance”,policy tool usage is relatively balanced,with close collaboration among policy entities.However,the theme of“AI Theoretical System”lacks a comprehensive understanding of tool usage and necessitates enhanced cooperation with other policy entities.Research limitations:The data sources and experimental scope are subject to certain limitations,potentially introducing biases and imperfections into the research results,necessitating further validation and refinement.Practical implications:The study introduces a three-dimensional analysis framework for disruptive technology policy texts,which is significant for formulating and enhancing disruptive technology policies.Originality/value:This study utilizes text mining and content analysis techniques to quantitatively analyze disruptive technology policy texts.It systematically evaluates China’s AI policies quantitatively,focusing on policy tools,policy actors,policy themes.The study uncovers the characteristics and deficiencies of current AI policies,offering recommendations for formulating and enhancing disruptive technology policies.

Voices that matter:The impact of patient-reported outcome measures on clinical decision-making

The critical role of patient-reported outcome measures(PROMs)in enhancing clinical decision-making and promoting patient-centered care has gained a profound significance in scientific research.PROMs encapsulate a patient's health status directly from their perspective,encompassing various domains such as symptom severity,functional status,and overall quality of life.By integrating PROMs into routine clinical practice and research,healthcare providers can achieve a more nuanced understanding of patient experiences and tailor treatments accordingly.The deployment of PROMs supports dynamic patient-provider interactions,fostering better patient engagement and adherence to tre-atment plans.Moreover,PROMs are pivotal in clinical settings for monitoring disease progression and treatment efficacy,particularly in chronic and mental health conditions.However,challenges in implementing PROMs include data collection and management,integration into existing health systems,and acceptance by patients and providers.Overcoming these barriers necessitates technological advancements,policy development,and continuous education to enhance the acceptability and effectiveness of PROMs.The paper concludes with recommendations for future research and policy-making aimed at optimizing the use and impact of PROMs across healthcare settings.

Economic effect of China's carbon neutrality target under shared socioeconomic pathways

Economic feasibility is crucial for achieving the carbon neutrality target.However,current integrated assessments often underestimate the economic impacts of mitigation policies due to the lack of consideration of their economic benefits.This study integrates a warming-labour productivity model with a typical integrated assessment model using shared socioeconomic pathways.It simulates China's economic development and carbon emission levels under both baseline and carbon-neutral policy scenarios,evaluating the economic costs and benefits of emission reduction policies aimed at achieving carbon neutrality.These findings reveal the following:(1)The economic costs of emission reduction policies are projected to peak between 2050 and 2060,ranging from 0.41%to 9.37%of total GDP in the baseline scenario,primarily due to increased energy prices and R&D investments.These costs are expected to decline rapidly after 2070.(2)China's carbon-neutral policies will mitigate global warming,with the economic benefits of mitigation projected to reach 5.65%to 17.24%of China's total GDP by 2100.(3)Lowcarbon scenarios SSP1 and SSP4 could significantly reduce initial economic costs and advance the onset of net economic gains to 2060.This integrated assessment confirms that China's carbon neutrality target offers substantial net economic benefits in the long term.To minimize initial economic costs,efforts should focus on enhancing consumption-side transitions,upgrading lowcarbon technologies,and adopting new energy sources.

Policy Gradient Adaptive Dynamic Programming for Model-Free Multi-Objective Optimal Control

Dear Editor,In this letter,the multi-objective optimal control problem of nonlinear discrete-time systems is investigated.A data-driven policy gradient algorithm is proposed in which the action-state value function is used to evaluate the policy.In the policy improvement process,the policy gradient based method is employed.

基于Meta分析的农业补贴政策对绿色生产的影响问题

针对现有研究对农业补贴政策的绿色促进效果存在争议的问题,基于52篇实证文献,33424个独立样本,运用Meta分析方法,计算农业补贴绿色促进效果的综合效应值;运用Meta回归方法,从地区层面、政策层面、生产层面、时期层面和方法层面5个维度,探究农业补贴政策对农户绿色生产存在的调节效应,分析异质性来源。研究结果表明:地区维度显示,非粮食主产区的补贴政策对绿色生产促进效果优于粮食主产区;政策维度显示,绿色农业补贴政策比传统农业补贴政策的绿色促进效果更好;生产维度显示,在补贴政策的惠及下,农户更愿意通过引入绿色生产技术的方式实现绿色生产;时期维度显示,2020年基本建成以绿色生态为导向的农业补贴政策体系后,农业补贴的绿色促进效果更好;方法维度显示,研究使用的计量模型种类在农业补贴政策对农户绿色生产影响的研究中具有调节效应。所得结论能够为我国农业补贴政策体系的转型升级实践提供理论依据。

Research on Policy Diffusion Path and Reproduction of River Chief System

The River Chief System (RCS) has evolved from local innovative practices to a national water governance strategy to address the current challenges in China’s water environmental management. In contrast to existing research that focuses on the strengths, weaknesses, and improvements of RCS, this study uses literature study to reveal the dynamic evolution of RCS through three phases, with RCS spreading from developed coastal areas to central and western inland regions. RCS’s diffusion path involves vertical diffusion between central and local levels and horizontal diffusion among local governments. Moreover, RCS has also achieved conceptual spillover, gradually expanding into other governance domains, such as the Lake Chief System, the Field Chief System, the Forestry Chief System, and the integration of multiple chief roles. However, it is essential to scrutinize the phenomenon of applying similar governance mechanisms to different areas, as it may result in challenges such as overburdening local governments, insufficient public participation, oversimplification of differences in natural resource endowments, and limited applicability. This study also provides suggestions on how to address these challenges. The study contributes theoretical insights and policy implications, providing a foundation for practical policy innovation.

Big Data Analysis of Policy Coordination Paths Based on Latent Dirichlet Allocation Model and Fuzzy-Set Qualitative Comparative Analysis Method

The selection and coordinated application of government innovation policies are crucial for guiding the direction of enterprise innovation and unleashing their innovation potential.However,due to the lengthy,voluminous,complex,and unstructured nature of regional innovation policy texts,traditional policy classification methods often overlook the reality that these texts cover multiple policy topics,leading to lack of objectivity.In contrast,topic mining technology can handle large-scale textual data,overcoming challenges such as the abundance of policy content and difficulty in classification.Although topic models can partition numerous policy texts into topics,they cannot analyze the interplay among policy topics and the impact of policy topic coordination on enterprise innovation in detail.Therefore,we propose a big data analysis scheme for policy coordination paths based on the latent Dirichlet allocation(LDA)model and the fuzzyset qualitative comparative analysis(fsQCA)method by combining topic models with qualitative comparative analysis.The LDA model was employed to derive the topic distribution of each document and the word distribution of each topic and enable automatic classi-fication through algorithms,providing reliable and objective textual classification results.Subsequently,the fsQCA method was used to analyze the coordination paths and dynamic characteristics.Finally,experimental analysis was conducted using innovation policy text data from 31 provincial-level administrative regions in China from 2012 to 2021 as research samples.The results suggest that the proposed method effectively partitions innovation policy topics and analyzes the policy configuration,driving enterprise innovation in different regions.

Mapping Climate Services for Disaster Risk Management: A Systematic Review and Research Gaps from a Policy Process Perspective

Climate services (CS) are crucial for mitigating and managing the impacts and risks associated with climate-induced disasters. While evidence over the past decade underscores their effectiveness across various domains, particularly agriculture, to maximize their potential, it is crucial to identify emerging priority areas and existing research gaps for future research agendas. As a contribution to this effort, this paper employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to review the state-of-the-art in the field of climate services for disaster risk management. A comprehensive search across five literature databases combined with a snowball search method using ResearchRabbit was conducted and yielded 242 peer-reviewed articles, book sections, and reports over 2013-2023 after the screening process. The analysis revealed flood, drought, and food insecurity as major climate-related disasters addressed in the reviewed literature. Major climate services addressed included early warning systems, (sub)seasonal forecasts and impact-based warnings. Grounded in the policy processes’ theoretical perspective, the main focus identified and discussed three prevailing policy-oriented priority areas: 1) development of climate services, 2) use-adoption-uptake, and 3) evaluation of climate services. In response to the limitations of the prevalent supply-driven and top-down approach to climate services promotion, co-production emerges as a cross-cutting critical aspect of the identified priority areas. Despite the extensive research in the field, more attention is needed, particularly pronounced in the science-policy interface perspective, which in practice bridges scientific knowledge and policy decisions for effective policy processes. This perspective offers a valuable analytical lens as an entry point for further investigation. Hence, future research agendas would generate insightful evidence by scrutinizing this critical aspect given its importance to institutions and climate services capacity, to better understand intricate facets of the development and the integration of climate services into disaster risk management.

Geographical Distribution of Atmospheric Nitrogen Deposition in China and Its Response to Emission Control Policy

Atmospheric nitrogen(N)deposition has experienced significant change because of anthropogenic emissions,thereby exerting a pronounced impact on global ecosystem services.With the rapid development of industry and agriculture and the swift expansion of urban areas in China since the 1980s,reactive nitrogen(Nr)emissions and N deposition have substantially increased.In pursuit of im-proving air quality,China has implemented a series of environmental protection policies and undertaken diverse measures to reduce pol-lutant emissions.This paper is a review of multivariate data sources of atmospheric N deposition based on the results of literature from 1980 to 2023,and the original data from 1980 to 2020 are summarized,counted and calculated.The main findings are as follows:1)the annual average atmospheric N deposition ranged from approximately 20-40 kg/(ha·yr),with the variability primarily linked to different assessment methods;2)regional disparities were evident in the spatial distribution of N deposition,with elevated values concentrated in areas with intense Nr emissions;3)atmospheric N deposition significantly declined after 2010,particularly the deposition of oxidized N,while reduced N deposition remained stable.These results reflect the effects of China's serious control policies on nitrogen oxide(NO.)emissions and strengthen the importance of agricultural NH3 emission mitigation.This study contributes to a comprehensive understanding of the N dynamics in the emission-deposition process,and provides a scientific foundation for the research of environmental protection,climate change,and sustainable development.

The Adjustment of NATO’s Space Policy and Its Implications

Under the US leadership,NATO has been adjusting its space policy and strengthening its space deterrence capabilities to address the so-called“threat”from China and Russia.While the deterrent effect of NATO’s space policy remains to be seen,the various measures taken to implement the policy will have a considerable impact on the global space landscape,accelerating the weaponization of space and making it more difficult to prevent an arms race in space and govern space security.

Perception Enhanced Deep Deterministic Policy Gradient for Autonomous Driving in Complex Scenarios

Autonomous driving has witnessed rapid advancement;however,ensuring safe and efficient driving in intricate scenarios remains a critical challenge.In particular,traffic roundabouts bring a set of challenges to autonomous driving due to the unpredictable entry and exit of vehicles,susceptibility to traffic flow bottlenecks,and imperfect data in perceiving environmental information,rendering them a vital issue in the practical application of autonomous driving.To address the traffic challenges,this work focused on complex roundabouts with multi-lane and proposed a Perception EnhancedDeepDeterministic Policy Gradient(PE-DDPG)for AutonomousDriving in the Roundabouts.Specifically,themodel incorporates an enhanced variational autoencoder featuring an integrated spatial attention mechanism alongside the Deep Deterministic Policy Gradient framework,enhancing the vehicle’s capability to comprehend complex roundabout environments and make decisions.Furthermore,the PE-DDPG model combines a dynamic path optimization strategy for roundabout scenarios,effectively mitigating traffic bottlenecks and augmenting throughput efficiency.Extensive experiments were conducted with the collaborative simulation platform of CARLA and SUMO,and the experimental results show that the proposed PE-DDPG outperforms the baseline methods in terms of the convergence capacity of the training process,the smoothness of driving and the traffic efficiency with diverse traffic flow patterns and penetration rates of autonomous vehicles(AVs).Generally,the proposed PE-DDPGmodel could be employed for autonomous driving in complex scenarios with imperfect data.

Tracking direct and indirect impact on technology and policy of transformative research via ego citation network

Purpose:The disseminating of academic knowledge to nonacademic audiences partly relies on the transition of subsequent citing papers.This study aims to investigate direct and indirect impact on technology and policy originating from transformative research based on ego citation network.Design/methodology/approach:Key Nobel Prize-winning publications(NPs)in fields of gene engineering and astrophysics are regarded as a proxy for transformative research.In this contribution,we introduce a network-structural indicator of citing patents to measure technological impact of a target article and use policy citations as a preliminary tool for policy impact.Findings:The results show that the impact on technology and policy of NPs are higher than that of their subsequent citation generations in gene engineering but not in astrophysics.Research limitations:The selection of Nobel Prizes is not balanced and the database used in this study,Dimensions,suffers from incompleteness and inaccuracy of citation links.Practical implications:Our findings provide useful clues to better understand the characteristics of transformative research in technological and policy impact.Originality/value:This study proposes a new framework to explore the direct and indirect impact on technology and policy originating from transformative research.

COMRADES FOREVER--To Lam’s visit demonstrates that China remains Vietnam’s top foreign policy priority

On August 20,2024,General Secretary of the Communist Party of Vietnam(CPV)Central Committee and Vietnamese President To Lam concluded his state visit to China.China was the destination for Lam's first overseas visit after taking office as general secretary of the CPV Central Committee,which clearly demonstrates that the heads of both countries attach importance to developing the bilateral relations and that Vietnam regards China as the strategic choice and top priority for its foreign policy.

Policy text quantification of urban waste classification from the perspective of policy tools:Based on the analysis of 6 cities in Northwest China

Based on the theory of policy tools and the application of content analysis method,this paper conducts a quantitative study on 32 samples of municipal waste classification policy texts in 6 cities in Northwest China.It constructs an analysis framework from the perspective of policy tools,policy contents and time series,and then measures and analyzes the policy texts according to the steps of defining analysis units,categories and coding,reliability and validity testing,etc.The results show that:(1)The urban waste classification policy in Northwest China is characterized by increasing attention year by year,a focus on government guidance and investment,and a clear division of responsibilities.These factors help to activate the motivation for policy implementation in cities across Northwest China,foster multi-departmental cooperation,and encourage active participation from various social entities in the process of implementing waste classification policies.(2)At the present stage,the design and application of policy tools are still unreasonable.On the one hand,the structure of policy tools is unbalanced,with excessive environmental policy tools leading to resource waste and insufficient demand policy tools leading to insufficient policy pulling power,which is not conducive to the long-term implementation of garbage classification management.At the same time,the internal structure of the secondary tools of the three types of policy tools is also uneven and unreasonable proportion further aggravates the waste of policy resources;On the other hand,the use of policy tools in each link of the policy content lacks focus and the concept of local policy implementation,which is difficult to meet the current practical needs and difficulties of garbage classification and treatment.According to this,the paper puts forward some policy suggestions,such as increasing the use of demand-oriented policy tools,paying attention to the reasonable matching of policy tools in various links of classification,and paying attention to the coordination of policy goal,process and result under the comprehensive dimension.

Moderating effect of corporate financialization on the impact of climate policy on corporate green innovation:Evidence from China

With intensifying global climate change,humanity is confronted with unparalleled environmental challenges and risks.This study employs the staggered difference-in-difference model to examine the relationship between climate policy and green innovation in the corporate financialization context.Using Chinese-listed company data from 2008 to 2020,our analysis reveals a favorable correlation between China’s carbon emission trading policy(CCTP)and advancements in green innovation.Furthermore,we find that the level of corporate financialization moderates this correlation,diminishing the driving effect of CCTP on green innovation.Additionally,results of heterogeneity analysis show that this moderating consequence is more evident in non-state owned and low-digitization enterprises compared with state-owned and high-digitization ones.Our findings contribute to the existing literature by clarifying the interaction between CCTP,green innovation,and corporate financialization.Our research provides valuable insights for policymakers and stakeholders seeking to strengthen climate policies and encourages green innovation in different types of businesses.

Paired Assistance:Policy Rationale and Economic Performance as Illustrated by Xizang and Xinjiang

This study highlights the changing priorities of China’s paired assistance throughout the past decades,as well as its theoretical implications and economic growth effects for recipient regions.Using panel data from 32 prefecture-level cities from 1990 to 2020,this study uses the multiperiod difference-in-differences approach to examine how paired assistance has contributed to economic growth in Xizang Autonomous Region and Xinjiang Uygur Autonomous Region.The findings indicate that,first,the implementation of the paired assistance policy has boosted economic growth in Xizang and Xinjiang.Second,paired assistance has stimulated economic growth in recipient communities by improving infrastructure.Third,paired assistance has contributed to economic growth in recipient communities by providing improved public services such as education and healthcare.Improvements to public services have a relatively smaller indirect effect in short term than infrastructure development on economic growth.Yet both education and healthcare are crucial to people’s quality of life in recipient communities.This paper has refined and broadened research on the effects of paired assistance,providing preference for future policymaking.