NetWork
Quantitative Policy Analysis and Implementation Effect Evaluation of Data Elements Driving Strategic Emerging Industries Development
LI Jinchang;ZHAO Zeyu;XIANG Ying;Giving full play to the fundamental resource role and innovation engine function of data elements to drive the high-quality development of strategic emerging industries is an inevitable requirement for accelerating the construction of Chinese modernization.This study follows a "from macro to micro" research logic to conduct a quantitative analysis of policies and an evaluation of implementation effects concerning data elements driving the development of strategic emerging industries.Utilizing the CogLTX long-text dynamic segmentation technology integrated with the BERTopic deep semantic modeling method,an in-depth mining and feature analysis is performed on 623 policy texts related to data elements driving strategic emerging industries from 2010 to 2024.On this basis,taking the core thematic module of "infrastructure support" as a typical case and further focusing on the "Broadband China" policy,the multiperiod difference-in-differences method is employed to empirically measure the impact of this policy on the structural upgrading of China's strategic emerging industries.The research findings indicate that:(1)During the sample period, policy themes for driving strategic emerging industries through data elements focuse on five major areas: "infrastructure support,industrial upgrading,market reform,technological breakthroughs,and financial assistance," demonstrating a three-stage policy evolution trend of "strategic deployment,supportive development,and coordinated integration."(2) The implementation of digital infrastructure support policies has a significant positive impact on the structural upgrading of strategic emerging industries.(3) Heterogeneity analysis and mechanism tests reveal that the positive impact of digital infrastructure support on the structural upgrading of strategic emerging industries is more pronounced in private enterprises,growth-stage enterprises,and the central and western regions.(4)Digital infrastructure support promotes the structural upgrading of strategic emerging industries by enhancing supply chain stability and reducing resource misallocation.Based on these conclusions,this study proposes policy recommendations centered on establishing a clear delineation of rights and responsibilities,implementing differentiated support strategies tailored to regional and firm-specific conditions,and harnessing data elements to enhance supply chain stability and optimize resource allocation.
Research on the Impact of New-Type Infrastructure on Industrial Structure Upgrading
MA Wei;HUI Ning;China 's economy has entered a stage of high-quality development.The continuous optimization of the economic structure is a prerequisite for steadily improving the quality and efficiency of economic growth.Industrial structure upgrading under high-quality development requires new drivers of growth.New-type infrastructure serves as a pivotal force in the digital economy era,comprehensively reshaping production relations and unleashing digital productivity.It can inject powerful momentum into China 's efforts to accelerate the formation of new quality productive forces and achieve industrial structure upgrading.Therefore, this paper starts from labor transfer channels and uses a three-dimensional analysis framework to explain the theoretical mechanism by which new-type infrastructure affects industrial structure upgrading, and proposes corresponding research hypotheses accordingly.Using panel data from284 prefecture-level and above cities in China from 2003 to 2023,this paper empirically studies the impact of new-type infrastructure on industrial structure upgrading,as well as the underlying transmission mechanisms,based on measuring the level of new-type infrastructure construction at the city level.The results show that new-type infrastructure has significantly promoted the upgrading of industrial structure.Specifically,the three categories of new-type infrastructure—information infrastructure,innovation infrastructure, and integrated infrastructure—each exhibit a clear enabling effect.This conclusion remains robust after taking into account the interference of endogeneity and undergoing a series of robustness tests.Mechanism analysis shows that new-type infrastructure enables China ' s industrial structure upgrading through labor transfer channels, including deepened labor division, optimized labor supply,and improved labor welfare.Heterogeneity analysis finds that the positive impact of new-type infrastructure on industrial structure upgrading is more pronounced in cities with stronger digital governance effectiveness and those at the two extremes of the industrial structure upgrading level.The findings not only provide empirical evidence for understanding the institutional environmental conditions under which new-type infrastructure plays a role, but also capture the structural characteristics of new-type infrastructure at different levels of industrial structure upgrading,which include "providing timely help", "marginal optimization",and "adding icing on the cake".This breaks the traditional perception of "inclusive" impact and provides a key basis for formulating differentiated and precise policies.The results of the spatial effect test show that endogenous spatial interaction effects in industrial structure upgrading objectively exist,and the positive spatial spillover effects of new-type infrastructure in the process of industrial structure upgrading have also been confirmed.Accordingly,it is proposed that while increasing investment in various types of new-type infrastructure, exploring differentiated development strategies for new-type infrastructure,unblocking channels for labor transfer,and maximizing the spatial positive externalities of new-type infrastructure are the key to driving industrial structure upgrading.
Research on The Enabling Effect of Platform Economy on Enterprise Value Based on Large Language Model
GUO Lu;YUAN Yingqian;WANG Zhenghai;In the era of digital economy,with the rapid development of information technology,platform economy has become a new engine of economic growth.It is urgent for enterprises to deeply integrate the development of platform economy with the improvement of their own value to lay a solid foundation for their long-term development.In order to deeply explore the impact of platform economy on enterprise value and explore its mechanism,this paper uses ERNIE grand language model and enterprise annual report to accurately identify the development of enterprise-level platform economy.On this basis,relevant data of China's A-share listed enterprises from 2013 to 2022 are used as samples to conduct empirical research.It is found that the development of platform economy significantly drives the improvement of enterprise value,and this conclusion is still valid after a series of robustness tests.Further mechanism analysis shows that on the one hand,the development of platform economy can drive the rise of enterprise value by improving enterprise innovation efficiency;On the other hand,it can promote the improvement of enterprise value by improving the total factor productivity of enterprises.This effect is more obvious in high-tech enterprises,non-labor-intensive enterprises and enterprises in the western region.The research in this paper provides empirical reference and policy enlightenment for in-depth understanding of the driving effect of platform economy development on enterprise value and promoting the deep integration of Digital platform and micro-enterprises,which has important theoretical and practical significance.
Extremal Dependence-based Climate Risk Regionalization and Derivative Portfolio Construction
MENG Shengwang;MA Ning;As global climate change intensifies,catastrophic climate risks pose a significant threat to socio-economic stability,particularly in geographically diverse and vulnerable countries like China.To address this challenge,the Chinese Actuaries Climate Index(CACI) is construted as a standardized,multidimensional metric that provides a quantitative measurement of regional climate risks at the prefecturelevel city scale using historical data on temperature,precipitation,drought,and wind speed.Existing research has largely relied on methods that overlook the spatial tail dependence structure of extreme events,which exacerbates systemic risk and limits the effectiveness of regional risk management.A novel climate risk regionalization method based on multivariate extreme value theory is proposed to fill this critical gap.The primary objective of this study is to model the tail dependence of climate risks across Chinese cities and apply this structure to optimize climate derivative portfolios,thereby providing a new,robust tool for managing systemic climate risk.The methodology employs an extremal graphical model,where cities are represented as nodes and their risk dependencies are represented as edges,to analyze the inter-regional dependencies of catastrophic climate risks.A novel EMTP2(Extremal Multivariate Total Positivity of order two) constraint and a spatial constraint are introduced to regularize the graph structure,ensuring a sparse,interpretable model focused on positive dependence.Spectral clustering is then applied to a composite similarity matrix,which innovatively combines both the extremal dependence and spatial information,to generate climate risk zones that account for both risk dependence and geographical consistency.To test the practical application of these zones,climate index options are constructed for each city whose payoffs are tied to the CACI.Empirical results validate the effectiveness of the methodology.The efficacy of the EMTP2 constraint in identifying conditional extremal independence is confirmed by comparing the model' s parameter matrices before and after its application.Furthermore, an evaluation of different spatial constraint matrices reveals that a matrix derived from moderate relaxation of the spatial adjacency matrix yields the best clustering performance.This finding indicates a pronounced spatial agglomeration effect of climate catastrophe risks,meaning high-risk areas are often geographically clustered.In the application part,analyzing the efficient frontiers of option portfolios demonstrates the effectiveness of spatial diversification.A portfolio strategically diversified across different risk zones achieves a superior risk-adjusted return on capital of 16.93 %, substantially outperforming a portfolio concentrated within a single,highly dependent zone(8.86 %),which is attributable to the low correlation of extreme events between the selected zones.In conclusion,a robust, dual-contribution framework is introduced,featuring both a novel climate index and a sophisticated risk zoning methodology.The findings underscore the critical importance of spatial diversification strategies,informed by tail dependence structures, in mitigating systemic risk and enhancing portfolio stability.Significant practical implications are offered not only for the pricing of insurance products and the strategic allocation of climate derivative portfolios,but also for guiding governmental disaster-preparedness planning and resilient infrastructure investment.
Research on Dynamic Economic Shock Effects of Industry Tail Risk Transmission:From a Production Network Perspective
REN Junfan;CUI Yanxin;CHEN Taofeng;XU Xiangyun;Methodologically,this investigation develops an innovative framework by incorporating an industrial tail risk factor into a comprehensive production network model.This sophisticated modeling strategy successfully identifies and distinguishes between two fundamental transmission mechanisms:the technical distortion network effect,which manifests through the propagation of productivity inefficiencies across interconnected industries, and the allocation distortion network effect,which operates through the cascading consequences of resource misallocation throughout the production ecosystem.The empirical analysis utilizes extensive datasets covering 44 distinct Chinese industries over the 1998-2020 period,meticulously compiled from the authoritative Inter-Country Input-Output(ICIO) database.To ensure robust examination of dynamic relationships, the research implements advanced econometric methodologies including Panel Vector Autoregression(PVAR) models and Time-Varying Parameter Stochastic Volatility Vector Autoregression(TVP-SV-VAR) techniques,enabling precise quantification of the differential temporal impacts exerted by these dual distortion effects on industrial value-added fluctuations.The empirical findings reveal several pivotal conclusions.First, both technical and allocation distortion network effects generate substantial short-term adverse consequences for China ' s economic performance,with the allocation distortion effect demonstrating particularly severe and immediate contractionary impacts due to its fundamental disruption of resource allocation efficiency.Second,the analysis identifies intermediate input substitutability as a crucial mitigating factor,suggesting that enhancing flexibility in production input utilization can effectively buffer against the negative value-added consequences of network-transmitted distortions.Third,and most significantly, extreme tail events function as powerful amplifiers of these transmission mechanisms,where even isolated technical deficiencies or resource misallocations within single industries can trigger extensive multiplier effects through input-output connections, ultimately generating persistent value-added deterioration across multiple industrial chain echelons.These insights fundamentally underscore the critical importance of recognizing production networks as potent conduits for risk amplification within modern economic systems.Consequently, the study proposes a comprehensive policy framework emphasizing the establishment of sophisticated risk monitoring and early-warning systems,strategic enhancement of supply chain resilience and adaptive capacity, systematic optimization of resource allocation mechanisms,and accelerated technological innovation and adoption.The effective implementation of these coordinated policy measures represents an essential prerequisite for constructing a secure, resilient,and self-reliant economic development paradigm capable of navigating the complex challenges characterizing the contemporary global economic landscape.
Research on the Spatiotemporal Evolution and Development Obstacles of New Quality Productive forces's Ecological Environment
XU Hao;FENG Tao;Accelerating the cultivation of new quality productivity is the key to China 's current economic transformation and upgrading,and optimizing the ecological environment for the development of new quality productive forces is the prerequisite for accelerating the cultivation of new quality productive forces.Firstly,based on the connotation of the Marxist concept of productive forces,this paper analyzes the ecological environment factors of the development of new quality productive forces from the perspective of innovation value chain.Then,an evaluation index system for the ecological environment of new quality productive forces is constructed from five dimensions:organizational competition,factor input,development output,market environment and policy incentives.Using data from 30 mainland provinces in China from2013 to 2022 as samples,entropy weight method,spatial Moran index,and obstacle degree model are used for analysis.The results show that the overall ecological environment level of China ' s new quality productive forces is on the rise,with the eastern region significantly better than the central and western regions,and the northeast region deteriorating year by year;In 2022,Guangdong,Jiangsu,and Zhejiang ranked among the top three,while Qinghai had the fastest development with an average annual growth rate of 4.496 %;The eight major economic zones have significant differences,showing a trend of relative convergence and absolute divergence,with the Northwest Economic Zone optimizing the fastest;The south is significantly better than the north,showing a relative and absolute dual trend of development between the north and the south;There is significant spatial agglomeration in the ecological environment of inter provincial new quality productive forces,with spatial agglomeration characteristics transitioning in provinces and cities such as Beijing,Hunan,and Jiangxi.The main obstacles to optimizing the ecological environment of new quality productive forces have shifted from insufficient infrastructure in 2013 to insufficient talent investment in 2022.Talent investment has become the main obstacle to the development of the eastern,central,and western regions,while the administrative environment is the main obstacle to the development of the Northeastern region.There are significant differences in regional and inter provincial obstacles,which need to be overcome according to local conditions.Finally,it is recommended to optimize the ecological environment according to local conditions by optimizing the talent ecology,improving the policy ecology,and enhancing the market ecology,in order to accelerate the formation of new quality productive forces.
Enterprise Digital Transformation,Supply Chain Spillover Effect and Employment Stabilization
HU Lei;WU Qiang;JIANG Zhener;Employment is the foundation of peoples livelihood,which bears on social stability and economic development.In the context of the booming development of the digital economy,digital transformation has not only emerged as a key path for enterprises to enhance competitiveness, but also has a profound impact on the job market.By improving production efficiency and expanding market size,digital transformation of enterprises can enhance their capacity to absorb employment.As collaboration within industrial and supply chains continues to gain importance,enterprises along the chain establish financial and business connections through their input-output relationships.Consequently,decisions made by one enterprise are transmitted to others along the chain, giving rise to supply chain spillover effects.Therefore,it is worth exploring whether the employment effects of digital transformation of enterprises can spill over along the supply chain.Using data from Chinese A-share listed companies from 2009 to 2022,this study empirically examines the impact and mechanism of digital transformation of suppliers on the labor employment scale client firms.It is found that digital transformation of suppliers significantly expands the scale of employment in clients.Mechanism tests indicate three primary channels:improving clients ' financial conditions,enlarging clients ' production scale,and enhancing clients ' market competitiveness.Heterogeneity analyses reveal notable differences across contexts.The employment expansion effect weakens when clients firms have higher levels routine task intensity or greater overstaffing,but is more pronounced among labor-intensive clients.The spillover is stronger when suppliers and clients operate in different industries or regions,and when clients are state-owned,high-growth,or high-productivity firms.The effect is also more prominent for clients located in regions with higher labor-market integration or those in Eastern China.The conclusion of this study provides a theoretical basis and empirical evidence to clarify the impact mechanism of supplier's digital transformation on the labor employment scale of clients.In light of this,four policy suggestions are proposed:accelerate the promotion of enterprises digital transformation, play the “multiplier" role of employment;strengthen the linkage effect of industrial and supply chains, improve the modernization level of industrial and supply chains;play the employment creation effect of digital transformation,prevent and resolve the impact of employment substitution;formulate differentiated support policies,and promote the effective linkage between digital transformation and stable employment.These suggestions provide important policy implications for promoting the deep integration of the real economy and digital economy,enhancing the modernization level of industrial and supply chains,and stabilizing and expanding employment scale.
Digital Infrastructure Construction and Coordinated Development of Urban "Carbon Reduction,Pollution Reduction,Green Expansion and Growth"
XIN Chongchong;LUO Yangfan;ZHONG Shunbin;Accelerating the construction of digital infrastructure is an important foundation for realizing the coordinated development of the urban "carbon reduction,pollution reduction,green expansion and growth".On the basis of theoretical explanation of the coordinated development of urban digital infrastructure construction in promoting urban "carbon reduction,pollution reduction,green expansion and growth",using the panel data of 282 cities at or above the prefecture level from 2006 to 2021,and based on the quasi-nature of "Broadband China" strategic demonstration city,this paper empirically investigates the role of digital infrastructure construction in promoting urban "carbon reduction, pollution reduction, green expansion and growth" by using DID method.The research finds that:firstly, the construction of urban digital infrastructure is helpful to promote the coordinated development of "reducing carbon,reducing pollution,green expansion and growth",and this conclusion still holds after a series of robustness tests and discussions on endogenous issues.Second,the construction of digital infrastructure has a stronger role in promoting the coordinated development of "carbon reduction,pollution reduction,green expansion and growth" in the eastern region,cities with high degree of cooperation,cities with good economic conditions and cities with high Internet level.Third,digital infrastructure construction promotes the coordinated development of "reducing carbon, reducing pollution, green expansion and growth" by promoting green technology innovation, strengthening environmental regulation and increasing government environmental protection expenditure.In this regard, it is suggested to continue to strengthen the construction of urban digital infrastructure and promote the development of digital economy;Adopt differentiated measures to advance the development of the digital economy in light of conditions;Enhance the breadth and depth of urban digital application,so that it can effectively promote the coordinated development of "carbon reduction,pollution reduction,green expansion and growth" in cities for a long time.
Research on the Mechanism and Effect of Data Elements Driving Corporate Green Transformation
SUN Panfeng;ZHUO Ronghai;TIAN Maozai;Green development refers to an economic growth and social development that aims at efficiency,harmony and sustainability,and its core lies in realizing a harmonious symbiosis between environmental protection and economic development,striving for a win-win situation.Currently Chinese enterprises still face two major challenges in their green transformation proess:insuffieient transformation momentum and inadequate capabilities.As a core element in the era of digital economy,can data elements drive the green transformation of enterprises? What are the paths of enterprise green transformation? Is there any heterogeneity?Answering the above questions is not only crucial for enterprises to innovate their production and operation methods and promote their green,high-quality and sustainable development,but also of great significance for promoting China ' s economic transition to green development,reaching the goal of "dual-carbon",and realizing high-quality and sustainable development of the economy.Therefore,this paper focuses on the above issues to carry out theoretical analysis and empirical verification.Therefore,this paper selects all A-share non-financial listed companies in China from 2011 to 2023 as the research samples,and uses the double fixed-effects regression model,based on the micro perspective to deepen the influence of micro-level data elements on China ' s corporate green transformation and its mechanism path.The study finds:First,data elements can effectively drive the green transformation of Chinese enterprises.Second,data elements can effectively alleviate the information asymmetry problem faced by enterprises,promote green technological innovation,and then drive the green transformation of enterprises.Third,government subsidies play a positive moderating role in the process of enterprise green transformation driven by data factors,the driving effect of data elements on enterprise green transformation is more significant in the central and western regions,non-heavily polluted enterprises and state-owned enterprises than in the eastern regions,heavily polluted enterprises and non-state-owned enterprises.Based on the conclusions of the previous study,this paper constructs a systematic solution from the three dimensions of institutional innovation,subject empowerment and policy synergy to provide a multidimensional practical path for fully releasing the multiplier effect of data elements in green transformation.It not only provides both theoretical depth and practical value of decision-making reference for enterprise green transformation in the era of digital economy,but also meets the requirements of the “dual-carbon”strategy and high-quality development,and provides a way to crack the structural contradiction in the "transition pain period",and helps our country build a modernized industrial system and a green development model.
Study on Statistical Data Quality and Survey Compilation of Green Finance
SHI Daimin;YU Lan;SHI Haoming;Green finance serves as a critical pillar for sustainable development and the Chinese modernization.In recent years,the rapid development of green finance in China has facilitated the transformation of the economy towards a higher level and quality,while also contributing to the achievement of carbon peaking and carbon neutrality goals.In the process of rapid development of green finance,statistical theory of green finance lags behind the practice of green finance.Although statistical theory and practice have been established for green financial products such as green credit,green insurance,and green bonds,there are still many issues that need to be explored in depth regarding the classification,framework,and measurement of green finance statistics.In particular,the standards and systems for green finance statistics are relatively fragmented,and the data is still in complete and of insufficient quality,there is a lack of a comprehensive statistical system that can thoroughly monitor the development of green finance.Compiling a green finance survey can effectively present fundamental data on the total volume and structure of green finance,which facilitates a comprehensive and systematic monitoring of green financial activities and aiding in the analysis and assessment of the development status of green finance.Therefore,following the logical requirements of green finance statistical monitoring,this paper aims to compile a green finance survey.Specifically,it examines several fundamental issues,including the classification of green finance statistics,the data foundation,and the challenges in compiling the survey and the flow of funds table.The findings indicate that the current classification of green activities in statistical standards and systems is mainly based on industrial levels.To meet the diverse demands for green finance from government departments,enterprises,the general public,it is necessary to classify green finance from multiple perspectives,including the degree of greenness and its effects,and conduct multi-level green finance total amount.And it is necessary to further refine and expand the scope of green finance statistics,extending the statistical perspective from financial institutions to multiple sectors involved in green finance activities.Additionally,efforts should be made to optimize and enhance the structure and quality of green finance data,involve systematically constructing a multi-dimensional green finance database and establishing a quality supervision system for green finance.Finally,by integrating the various specialized statistical standards and systems of green finance,the compilation of a green finance survey and flow of funds table is proposed.These tools are designed to reflect the specific manifestations of green finance flows and stocks at different classification levels,providing an effective solution to the current lack of comprehensive green finance statistics.The research results are helpful to improve the statistical theory of green finance and provide some references for establishing a comprehensive statistical system of green finance.