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Sponsor: Shaanxi Provincial Department of Education
Sponsored by：Xi'an University of Finance and Economics
Higher Education Branch of China Statistical Education Society
Director: ZHAO MINJUAN
Vice Director: LI JIAORUI ZHAO YANYUN
Publisher: Editorial Department of Journal of Statistics and Information
Address:No. 64, XiaozhaiEast Road, Yanta District, Xi’an, China
Post Code：710061
E-mail: tjyxxlt@126.com
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Social Cost of Carbon,Liability Differences,and Fair Accounting of Global Carbon Emissions
WANG Jing;LUO Liangqing;WANG Siming;XU Feiyang;The principle of “common but differentiated responsibilities” underpins global climate governance,operationalized through differentiated carbon pricing. Prevailing carbon accounting,based on homogenous emissions assumptions,overlooks liability disparities arising from carbon price variations,risking equalization of mitigation duties. This study incorporates regional heterogeneity in carbon prices,proposing an international accounting framework adjusted by social cost of carbon(SCC) differentials,and reassesses China's cooperative priorities. Findings show:(1) The SCC-adjusted framework captures responsibility gaps between developed and developing countries(regions) due to divergent development and technology levels, balancing equity and efficiency via marginal damage costs.(2) China's adjusted emissions fall below conventional estimates but remain globally high due to domestic demand, with electricity,gas,and water supply ranking top across all perspectives.(3) Priority partners are China's Hong Kong,South Korea,and Ethiopia,focusing on manufacturing and energy. This framework accommodates development disparities and mitigation efforts,informing negotiations and policy. Applied economies,it requires enhanced tech and financial support for data-sparse regions,alongside tailored mitigation targets.
Measurement of Employment Effects of Patent-Intensive Industries Based on the Input-Output Framework
XU Aiting;SU Zitian;LIANG Yanyan;As a key driver of high-quality full employment,patent-intensive industries require systematic analysis of the employment effects induced by household consumption. This study first compiles sequential input-output tables for patent-intensive industries from 2012 to 2023,then constructs a 74-sector semi-closed input-output model incorporating the household sector,and finally measures their employment effects and transmission pathways. The results show that patent-intensive industries have exerted a steadily increasing driving effect on employment in China. They maintain strong production dependence on traditional industries,while their employment structure is shifting from traditional-industry dominance toward greater self-driven growth. By pathway,the innovation spillover pathway remains the dominant source of employment contribution,although its share has declined year by year; meanwhile,the contributions of the innovation self-driven pathway and the reverse spillover pathway both show fluctuating upward trends. Further analysis indicates that patent-intensive industries have steadily strengthened their employment-driving effects on technology-intensive and capital-intensive industries,promoting growth in high-skilled jobs and employment structure upgrading. Therefore,it is necessary to strengthen patent commercialization and industrial chain coordination,improve the “employment—income—consumption—production—employment” feedback mechanism,and address the substitution risks of artificial intelligence and other new technologies through vocational training,job transitions,and skill upgrading,so as to promote both employment expansion and structural upgrading.
The Asymmetric Impact of Government Subsidies on Corporate Capacity Utilization
BI Yu;NING Peipei;ZHANG Jie;Government subsidies,as an important policy instrument for guiding corporate production and operation,are widely adopted to incentivize technological innovation and promote the optimization and upgrading of production capacity. However,their actual effectiveness and boundary conditions still require rigorous empirical testing. Using Chinese A-share listed companies on the Shanghai and Shenzhen Stock Exchanges from 2007 to 2021 as the research sample,this paper differentiates R&D subsidies from nonR&D subsidies and systematically examines their distinct mechanisms and asymmetric effects on corporate capacity utilization. The findings show that government R&D subsidies and non-R&D subsidies exert asymmetric effects on corporate capacity utilization: R&D subsidies significantly suppress capacity utilization,whereas non-R&D subsidies have an inverted U-shaped effect on it,and these conclusions remain robust after a series of robustness checks. Mechanism analysis indicates that the suppression effect of R&D subsidies on capacity utilization is mainly driven by credit distortion and capital misallocation,while non-R&D subsidies affect capacity utilization through credit distortion, factor market distortion and the crowding-out of innovation. Heterogeneity analysis reveals that the effect of government subsidies on capacity utilization differs between high-tech and non-high-tech firms:the negative effect of R&D subsidies is observed only in non-high-tech firms,whereas for high-tech firms R&D subsidies help improve capacity utilization. Moreover,this adverse effect is concentrated in firms with stronger political connections,higher industry concentration and larger scale. Further decomposition of non-R&D subsidies shows that tax rebates and financial rewards play a dominant role in shaping capacity utilization. The conclusions contribute to a deeper understanding of the relationship between government subsidies and capacity utilization,providing empirical insights for the government to optimize subsidy policies and vigorously develop new quality productive forces.
Measurement and Characteristic Identification of Low-Income Groups in China
HONG Xingjian;LIU Jiali;ZHU Xuebo;PAN Meiying;The establishment of a tiered and categorized assistance system for low-income populations was proposed by the Third Plenary Session of the 20th Central Committee of the Communist Party of China. Based on the hierarchical poverty index, a hybrid low-income index is developed to empirically explore the types and scales of China's low-income groups during 2012-2022, with the random forest algorithm applied to capture population characteristics across different income stages. The study finds that the overall low-income group shows a downward trend,the proportion of low-income groups in rural areas is higher than that in urban areas,and with the implementation of poverty alleviation work and the work of “raising the income of the low-income population”, the absolute low-income population is gradually eliminated, and the relative low-income population gradually emerges. In addition, the proportion of different income sources is the primary feature distinguishing various types of low-income groups, the educational attainment of family members is an important differentiating factor, and the household expenditure structure reflects the specific type of a low-income group. Finally,based on the results of model fitting,this paper deeply analyzes the characteristics and causes of different types of low-income groups, and puts forward suggestions for increasing the income of different types of low-income groups and helping them enter the middle-low income group.
Evolution of China's Economic Growth Drivers:A Demand-Side and Supply-Side Structural Decomposition
JIN Jian;LIU Lu;WANG Mingjun;The accelerated development of emerging industries and the improvement in the quality of input factors are triggering profound changes in the dynamic mechanism of China's economic growth.This study compiles China's incremental input-output tables for strategic emerging industries from 2011 to 2025;constructs a sector-level decomposition framework for economic growth drivers focused on strategic emerging industries based on the Leontief production function and the Ghosh allocation function from input-output modeling;and applies structural decomposition analysis to conduct row-wise and column-wise decomposition of output changes.This approach separately analyzes the growth drivers of China's strategic emerging industries and the overall national economy from the supply side and the demand side,thereby clarifying the mechanism through which strategic emerging industries propel national economic development.The research findings are as follows.First,the input-output theoretical price model can effectively improve the compilation quality of input-output tables.Second,demand-side and supply-side changes in techno-economic linkages synergistically promote the development of strategic emerging industries and lead the sustained growth of the overall national economy.Third,during the 14th Five-Year Plan period,the contribution share of demand-side techno-economic linkage changes in strategic emerging industries to the total demand-side techno-economic linkage changes of the national economy surpassed that of traditional industries,signifying that demand-side techno-economic linkage changes have taken the lead in completing the critical transition from traditional factor-driven to innovation-driven growth.Fourth,labor factor input and the increase in social net income are key factors for the development of strategic emerging industries and also important channels through which strategic emerging industrial sectors drive national economic growth.Based on these findings,it is recommended that during the 15th Five-Year Plan period,coordinated efforts on both the supply and demand sides of the science and technology innovation chain be promoted,talent cultivation be prioritized,policy support be strengthened,and the sustained and healthy development of strategic emerging industries be leveraged to spearhead industrial transformation and propel the high-quality development of the overall national economy.
Nonlinear Contagion Network Construction and Early Warning Research of Systemic Financial Risk:Based on Tail Risk Dependence and Network Topology Analysis
OUYANG Zisheng;QIN Tian;DENG Yaoxun;Cross-institutional and cross-industry contagion of tail risks constitutes a critical trigger that destabilizes the financial system and induces systemic financial risks.Clarifying its contagion mechanism and realizing accurate risk early warning serves as an important guarantee for safeguarding the bottom line of financial stability and balancing development and security.Therefore,based on complex network theory and deep learning theory,this study uses the quantile regression-based CoVaR method to measure the tail risks of 59 financial institutions in China,and employs the HD-TVP-VAR model to construct a tail risk contagion network and systematically analyze its topological characteristics.Finally,it combines network topology indicators with deep learning models to conduct tail risk early warning.The results show that the tail risk network constructed based on the HD-TVP-VAR model can effectively characterize the nonlinear and time-varying characteristics of tail risk contagion among institutions,and shocks from major risk events can significantly raise the co-movement of tail risks among financial institutions.Network topological indicators efficiently identify core nodes and critical transmission paths of tail risk propagation,while a differentiated risk transmission pattern exists within the financial system:the banking sector acts as the primary net receiver of risks,whereas the insurance and real estate sectors function as major net risk transmitters.The macroeconomic impacts of tail risks are asymmetric under different network structures,and network density and global network efficiency are the main amplification channels through which tail risks exert shocks on the macroeconomy.Integrating early warning indicators such as macro market information,financial institution information and tail risk correlation information,the CNN-BiLSTMAttention model can significantly improve tail risk prediction accuracy.Therefore,it is necessary to strengthen the supervision of key risk nodes and risk early warning,enhance the resilience of the financial system against risks,so as to maintain financial system stability and achieve a dynamic balance between stable macroeconomic growth and risk prevention in the financial system.
[Downloads: 317 ] [Citations: 0 ] [Reads: 17 ] HTML PDF Cite this article
Institutional Openness and Firms' Labor Share:A Theoretical Model and Empirical Evidence
YANG Hang;AI Xiaoqing;As testbeds for institutional openness,the Pilot Free Trade Zones(PFTZs) affect the national labor share by expanding openness and unlocking institutional gains.The Diamond-MortensenPissarides framework is extended to model how PFTZs policies affect firms' labor shares,and the resulting predictions are tested using a staggered difference-in-differences design.The results show that establishing PFTZs significantly raises firms' labor shares, a finding robust to instrumental-variable estimation,heterogeneity-robust estimators, and other checks.Mechanism tests indicate that PFTZs raise labor shares by strengthening market competition,curbing capital deepening,reducing tax burdens,and lowering management costs.The effects are stronger for labor-intensive,small and medium-sized, and lowproductivity firms, as well as for priority liberalization sectors such as oil and gas, biomedicine,financial leasing,and global repair services.Regionally,the effects are significant in eastern coastal and inland areas but insignificant in border regions.Further analysis shows that AI adoption and the use of data as a factor of production both attenuate the positive effect of PFTZs on firms ' labor shares.PFTZs also raise average pay per employee and average pay for nonmanagerial workers,while lowering average managerial pay and within-firm wage inequality.By identifying an institutional-cost channel,the study broadens existing explanations of how PFTZs affect the labor share and offers policy implications for advancing common prosperity and Chinese modernization.
[Downloads: 360 ] [Citations: 0 ] [Reads: 45 ] HTML PDF Cite this article
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.
[Downloads: 1,079 ] [Citations: 0 ] [Reads: 35 ] HTML PDF Cite this article
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.
[Downloads: 2,399 ] [Citations: 0 ] [Reads: 62 ] HTML PDF Cite this article
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.
[Downloads: 2,836 ] [Citations: 0 ] [Reads: 42 ] HTML PDF Cite this article
A Review of Technologies on Random Forests
FANG Kuang-nana,b,WU Jian-bina,ZHU Jian-pinga,b,SHIA Bang-changa,b(a.Department of Statistics,School of Economics;b.Data Mining Center,Xiamen University,Xiamen 361005,China)Random Forests is a statistical learning theory,using bootsrap re-sampling method form sample sets,and then combining the tree predictors by majority voting so that each tree is grown using a new bootstrap training set.It is widely applied in medicine,bioinformatics,economics and other fields,because of its high prediction accuracy,good tolerance of noisy data,and the law of large numbers they do not overfit.In this paper we first introduce the concept of random forest and the latest research,then provide some important aspects of applications in economics,and a summary is given in the final section.
[Downloads: 48,490 ] [Citations: 2,563 ] [Reads: 205 ] HTML PDF Cite this article
Analysis on the Reliability and Validity of Questionnaire
ZENG Wu-yi~1,HUANG Bing-yi~2(1.School of Economics,Xiamen University,Xiamen 361005,Fujian;2.School of Management,Xiamen University,Xiamen 361005,Fujian)Study on the reliability and validity of the questionnaire has always been neglected in many(questionnaire) surveys in China.This paper mainly investigates the reliability and validity of a questionnaire and their evaluating methods.It also simply introduces how to use SPSS software to analyze the reliability and(validity) of a questionnaire.
ESG Performance,Institutional Investor Preference and Firm Value of Listed Companies
BAI Xiong;ZHU Yi-fan;HAN Jin-mian;To explore whether the ESG practices of listed companies can create value for the company and whether institutional investors in the capital market have ESG investment preferences will help companies recognize, participate in and practice the concept of ESG sustainable development.Based on the data of 3 400 A-share listed companies in Shanghai and Shenzhen Stock Exchange from 2013 to 2020,the shareholding ratio of institutional investors is introduced to explore the mechanism of ESG performance affecting corporate value and analyze whether institutional investors have ESG investment preference on this basis.The results are as follows:(1) ESG has the function of value creation.Good ESG performance of listed companies can significantly enhance their corporate value.(2) Attracting institutional investors to increase their shares is one of the ways for listed companies to enhance corporate value through ESG practice, and the proportion of institutional investors plays a partial intermediary role in the process of ESG influencing corporate value.(3) Institutional investors have a preference for ESG investment, and to a certain extent, they can tolerate low short-term operating performance of listed companies with good ESG performance All the above conclusions are robust.In the extended study, it is found that there is no heterogeneity in the value creation function of ESG between state-owned and non-state-owned listed companies.The preference of institutional investors ESG has heterogeneity in property rights and industry.Institutional investors prefer the listed companies with good performance of ESG in the secondary and tertiary industries and non-state-owned enterprises.Based on the research conclusions, suggestions are puts forward to accelerating the top-level design of ESG information disclosure and regulatory standards, encouraging companies to strengthen information disclosure, and cultivating medium and long-term institutional investors, which will help build and improve China's ESG development ecosystem and promote high-quality development.
[Downloads: 24,351 ] [Citations: 1,068 ] [Reads: 167 ] HTML PDF Cite this article
A Summary of Machine Learning and Related Algorithms
CHEN Kai1,ZHU Yu1,2(1.School of Statistics,Renmin University of China,Beijing 100872,China;2.Xi'an University of Finance & Economic,Xi'an 710061,China)Since the computer was invented,people have been wanted to know that whether it can learn.Machine learning is essentially a multidisciplinary field. It absorbed some results of artificial intelligence,probability and statistics,computational complexity theory,control theory,information theory,philosophy,physiology,neurobiological.This paper mainly based on statistical learning wanted to give a brief review and presentation to the perspective of machine learning and the development of related algorithms.
[Downloads: 28,808 ] [Citations: 681 ] [Reads: 234 ] HTML PDF Cite this article
Measurement of China's Provincial Digital Economy and Its Spatial Correlation
JIN Can-yang;XU Ai-ting;QIU Ke-yang;Based on the input-output perspective of economic systems, the index measurement system of digital economy development level is constructed from five dimensions: digital infrastructure, digital innovation, digital governance, digital industrialization and industrial digitization by combining the fuzzy set idea, and the weights are determined and compiled with the help of the vertical and horizontal pull-off method for China's provincial digital economy development index from 2012 to 2019.Based on this, the modified gravitation model is used to measure the spatial correlation intensity of the provincial digital economy development level, and the social network analysis is used to reveal the overall shape, internal structure, and evolutionary trend of the digital economy correlation network.The results are shown as follows.(1) The overall development of the digital economy across the country is on the rise, but the “Matthew effect” and “digital divide” are obvious, with the level of digital economy development decreasing from the eastern coast to the western inland.(2) The initial formation of a network of digital economy linkages, the agglomeration and spillover effects in various regions have gradually increased, and the mobility of digital resource elements in the province has been greatly enhanced.(3) Guangdong, Jiangsu, Beijing and other eastern provinces, as structural hole occupiers, have information and resource control advantages in the development of the digital economy, and Henan, Shaanxi and Sichuan, which have faster rate of effective scale and limit system enhancement, are seen as potential occupiers of structural holes.(4) The development of the digital economy is characterized by a clear aggregation of small groups, with four cohesive subgroups formed at the provincial level, and the linkage within the subgroups is significantly stronger than the external influence.(5) Due to geographical location, climatic conditions and other factors, there is less communication among members within the Northwest subgroup, and the density within its subgroup is lower than that of the whole network, and its internal digital economy tie needs to be further strengthened.The research findings have important implications for promoting the construction of a new pattern of digital economy development in China.
[Downloads: 14,590 ] [Citations: 634 ] [Reads: 177 ] HTML PDF Cite this article
A Review of Technologies on Random Forests
FANG Kuang-nana,b,WU Jian-bina,ZHU Jian-pinga,b,SHIA Bang-changa,b(a.Department of Statistics,School of Economics;b.Data Mining Center,Xiamen University,Xiamen 361005,China)Random Forests is a statistical learning theory,using bootsrap re-sampling method form sample sets,and then combining the tree predictors by majority voting so that each tree is grown using a new bootstrap training set.It is widely applied in medicine,bioinformatics,economics and other fields,because of its high prediction accuracy,good tolerance of noisy data,and the law of large numbers they do not overfit.In this paper we first introduce the concept of random forest and the latest research,then provide some important aspects of applications in economics,and a summary is given in the final section.
[Downloads: 48,490 ] [Citations: 2,563 ] [Reads: 205 ] HTML PDF Cite this article
A Summary of Machine Learning and Related Algorithms
CHEN Kai1,ZHU Yu1,2(1.School of Statistics,Renmin University of China,Beijing 100872,China;2.Xi'an University of Finance & Economic,Xi'an 710061,China)Since the computer was invented,people have been wanted to know that whether it can learn.Machine learning is essentially a multidisciplinary field. It absorbed some results of artificial intelligence,probability and statistics,computational complexity theory,control theory,information theory,philosophy,physiology,neurobiological.This paper mainly based on statistical learning wanted to give a brief review and presentation to the perspective of machine learning and the development of related algorithms.
[Downloads: 28,808 ] [Citations: 681 ] [Reads: 234 ] HTML PDF Cite this article
Analysis on the Reliability and Validity of Questionnaire
ZENG Wu-yi~1,HUANG Bing-yi~2(1.School of Economics,Xiamen University,Xiamen 361005,Fujian;2.School of Management,Xiamen University,Xiamen 361005,Fujian)Study on the reliability and validity of the questionnaire has always been neglected in many(questionnaire) surveys in China.This paper mainly investigates the reliability and validity of a questionnaire and their evaluating methods.It also simply introduces how to use SPSS software to analyze the reliability and(validity) of a questionnaire.
ESG Performance,Institutional Investor Preference and Firm Value of Listed Companies
BAI Xiong;ZHU Yi-fan;HAN Jin-mian;To explore whether the ESG practices of listed companies can create value for the company and whether institutional investors in the capital market have ESG investment preferences will help companies recognize, participate in and practice the concept of ESG sustainable development.Based on the data of 3 400 A-share listed companies in Shanghai and Shenzhen Stock Exchange from 2013 to 2020,the shareholding ratio of institutional investors is introduced to explore the mechanism of ESG performance affecting corporate value and analyze whether institutional investors have ESG investment preference on this basis.The results are as follows:(1) ESG has the function of value creation.Good ESG performance of listed companies can significantly enhance their corporate value.(2) Attracting institutional investors to increase their shares is one of the ways for listed companies to enhance corporate value through ESG practice, and the proportion of institutional investors plays a partial intermediary role in the process of ESG influencing corporate value.(3) Institutional investors have a preference for ESG investment, and to a certain extent, they can tolerate low short-term operating performance of listed companies with good ESG performance All the above conclusions are robust.In the extended study, it is found that there is no heterogeneity in the value creation function of ESG between state-owned and non-state-owned listed companies.The preference of institutional investors ESG has heterogeneity in property rights and industry.Institutional investors prefer the listed companies with good performance of ESG in the secondary and tertiary industries and non-state-owned enterprises.Based on the research conclusions, suggestions are puts forward to accelerating the top-level design of ESG information disclosure and regulatory standards, encouraging companies to strengthen information disclosure, and cultivating medium and long-term institutional investors, which will help build and improve China's ESG development ecosystem and promote high-quality development.
[Downloads: 24,351 ] [Citations: 1,068 ] [Reads: 167 ] HTML PDF Cite this article
Research on the Impact of R&D Investment and Government Subsidy on Enterprise Innovation Performance
WANG Xi;ZHANG Qiang;HOU Jia-xiao;China's demographic dividend has gradually weakened, and the shortcomings of the manufacturing industry have begun to become prominent.In this context, the urgent needs of enterprise innovation, backward technology and production capacity changes can be changed in order to achieve a healthy development of the manufacturing industry.Select the financial data of 692 listed manufacturing companies in the A-share market from 2015 to 2019,and use a panel data model to study the internal relationship between government subsidies, R&D investment and innovation performance of listed manufacturing companies.The results show that: government subsidies and R&D investment are positively correlated with enterprise innovation performance.For manufacturing enterprises, it is necessary to improve the effect of government subsidies on the innovation performance of manufacturing enterprises through measures, such as establishing and improving the subsidy pre-investigation system, increasing subsidies, strengthening the supervision of subsidy funds, and expanding subsidy channels.By increasing the level of R&D investment, establish and improve the internal control system and formulate R&D plans to give full play to the role of government subsidies in promoting enterprise innovation performance.
[Downloads: 15,160 ] [Citations: 502 ] [Reads: 370 ] HTML PDF Cite this article
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