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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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Mixed-frequency Varying-coefficient Quantile Model and Its Application in Risk Prediction
WANG Jiangtao;JIN Wu;LIU Hong;ZHOU Xiyu;Based on an in-depth analysis of the evolutionary characteristics of financial market risks,low-frequency trend variables with high-frequency trading information and a class of mixed-frequency varying-coefficient quantile models are integrated for risk prediction.The newly proposed mixed-frequency varying-coefficient quantile model has the following features:First,the new model is not only an extension of existing parametric mixed-frequency data processing methods in the direction of semi-parametrics,but also an expansion of ordinary varying-coefficient quantile models in the analysis of mixed-frequency data;The mixed-frequency varying-coefficient quantile model designs coefficients as functions of low-frequency trend variables,which not only leverages the advantages of varying-coefficient models in handling mixedfrequency data and overcomes potential model misspecification issues of existing parametric mixedfrequency data processing methods,but also provides a way to utilize mixed-frequency data information within the framework of ordinary varying-coefficient quantile models.Second,the new model can fully utilize mixed-frequency data information and reasonably characterize the dynamic characteristics of risk evolution rules,thus achieving better prediction performance;Comparisons of prediction results across multiple models show that the mixed-frequency varying-coefficient quantile model can predict risks more accurately,and this advantage is more prominent in the prediction of medium-and long-term risks.Third,the estimators of coefficients in the new model have asymptotic variances with a unique structure;Compared with traditional varying-coefficient quantile models,the locally linear estimators of coefficients in the mixed-frequency varying-coefficient quantile model have an additional term in their asymptotic variances,which is caused by the mixed-frequency phenomenon existing in the data and is elaborated in detail through theoretical analysis and simulation tests in the paper.The proposal of the new model not only serves as a valuable supplement to existing mixed-frequency data processing methods and varyingcoefficient models,but also provides technical support for making full use of mixed-frequency data information to forecast medium and long-term risks,thereby effectively preventing and resolving risks.
The Policy Effect of Changing from Business Tax to VAT on Improving the Accuracy of Industry Classification Statistical Data
XU Yonghong;XUE Zhaoqin;JIANG An;Since 2016,China's transition toward high-quality economic development and its pursuit of mutually beneficial international cooperation have heightened the demand for precise economic and social governance.Policymakers and scholars alike are increasingly calling for macro-statistical data that are more accurate,detailed,and aligned with international standards.However,statistical accuracy continues to be affected by industry classification practices formed during earlier periods of rapid growth,when mixed operational structures were common.A key source of inaccuracy lies in the misclassification of auxiliary service activities within enterprises.In China,auxiliary units are typically classified according to the primary industry of their parent enterprise.This practice,however,diverges from the 2008 System of National Accounts(SNA 2008),which stipulates that auxiliary units that are geographically separate or maintain independent accounts should be recorded as distinct statistical entities,even without independent legal personality.This study focuses on how China's "Business Tax to Value-Added Tax Reform"(B2V Reform)addresses this statistical discrepancy.The reform reduced the tax burden on smaller auxiliary units by shifting them from the business tax regime to the value-added tax system,distinct from their parent enterprises.This change creates a strong economic incentive for firms to legally separate their auxiliary service departments.As a result,the reform promotes more accurate industry classification,especially for diversified enterprises in sectors such as manufacturing and mining,whose core activities involve tangible goods production.Given these economic-statistical linkages,the B2V Reform offers a valuable opportunity to evaluate the accuracy of industry classification data and to inform adjustments to historical statistical records.Using provincial panel data from 2003 to 2021,this study applies a three-dimensional time-based analytical framework to empirically assess the impact of the B2V Reform on the accuracy of industry classification data and to examine variations across sectors.Exploratory adjustments are also made to relevant historical data.These findings indicate that the reform significantly improved data accuracy in pilot industries during its initial phase,while its effect on other industries in later stages was more limited.Heterogeneity analysis reveals that the reform had the strongest impact on the "information transmission,software,and information technology services" industry and the "leasing and business services" industry.After historical data adjustment,employment figures in these two corrected sectors-based on urban nonprivate units-exceed the originally reported values.This outcome confirms that the B2V Reform helps mitigate the underestimation of historical data in related service industries.Overall,this study validates the role of the B2V Reform in improving the accuracy of industry classification data.The findings are expected to help reduce statistical discrepancies in China's official practice and to provide a useful reference for the National Bureau of Statistics in revising economic statistical data.
Digital Technology Innovation and Spatial Correlation Network of High-quality Economic Development
LI Sufang;SONG Luyao;LI Xiaoping;During the 15th Five-Year Plan period,China's high-quality economic development has entered a critical phase,with digital technology innovation emerging as a key driver of structural transformation and the release of development momentum.To assess the spatial network linkages of highquality economic development in China from multiple frequency-domain perspectives,this study combines a spatio-temporal entropy-weighted TOPSIS approach with a Bayesian TVP-VAR-BK connectedness model.It also combines the patent database of the National Intellectual Property Administration to examine the impact effect and mechanism of digital technology innovation on the spatial network correlations.The results show that:(1) Compared to the short term,spatial network interconnectivity in the long term and across the entire cycle is relatively similar,and the spatial spillover effects of high-quality economic development among economic entities exhibit a certain degree of lag.(2) China's regions can be divided into three major functional blocks:the eastern region serves as the "primary radiating" block;the central region plays a "bridging" and intermediary role in regional linkages;and the western region acts as the "primary beneficiary" block.(3) Digital technological innovation significantly strengthens the spatial linkages of high-quality economic development across regions;its effects manifest over a longer time horizon,with stronger impacts observed in central regions and areas not reliant on natural resources.Mechanism analysis reveals that digital technological innovation enhances spatial network connectivity by promoting the interregional mobility of production factors.Meanwhile,the advancement of new digital infrastructure further strengthens the positive role of such innovation in improving network connectivity.Therefore,a sound policy system for differentiated regional collaboration should be established.Efforts should be made to enhance the cross-regional flow of production factors and the coordinated construction of digital infrastructure,and to improve the long-term incentive mechanism for regional innovation collaboration.Continuous efforts should be made to enhance the spatial linkage effect of high-quality economic development.
Analysis of Agglomeration Situation and Influencing Factors of New Agricultural Formats:Based on the Perspective of Endowment Structure
ZHAO Luben;DONG Kaijin;LIN Hai;LIANG Dong;New agriculture formats,formed through the deep integration of digital technologies and traditional agriculture,plays an increasingly important role in promoting the transformation,upgrading of traditional agriculture,and ensuring sustainable agricultural development.Using the business types and operational scopes of firms within the industry as the classification criteria,we evaluate the clustering levels of new agriculture formats enterprises across China's counties from 2000 to 2024.Examining the spatial distribution patterns and clustering dynamics of these enterprises.Meanwhile by applying cluster analysis and quantile regression models,we further investigate the critical role of factor endowment structures in shaping the agglomeration of new agriculture formats,as well as the heterogeneity of such effects across different levels of agglomeration.The results show that:(1)During the observation period,the agglomeration level of new agriculture formats across counties continuously increased and gradually exhibited a multi-polarized distribution pattern.Regionally,these industries tended to concentrate in capital-intensive areas such as the central-eastern regions,the Yangtze River Delta,and the Pearl River Delta,whereas their clustering in land-intensive regions was relatively weak.(2)Further analysis demonstrates that factor endowment structures are key determinants of agglomeration,with relatively abundant capital being the most decisive factor,followed by labor,and finally land.(3)The effects of factor structures on agglomeration exhibit clear heterogeneity across different quantiles,with the importance of capital rising further as agglomeration levels increase.Therefore,local governments should formulate development strategies for new agriculture formats in line with their regional factor endowment characteristics to avoid resource misallocation resulting from blind transformation.At the same time,by cultivating high-level regional technology diffusion hubs,governments can promote coordinated development of new agriculture formats and foster a complementary and synergistic new agglomeration pattern.
Research on a Bi-level Risk Budgeting Portfolio Model Based on ESG Integration
JING Kui;Practicing the ESG investment philosophy is not only a proactive response to China's "dual carbon" strategic goals,but also a crucial avenue for mitigating "green swan" risks,enhancing market reputation,and ensuring the sustainability of investment returns.Existing ESG portfolio models fail to fully integrate market information to cope with market uncertainty,and they struggle to achieve rational allocation and precise management of portfolio risk.This paper moves beyond the common integration approaches in ESG portfolio strategies and constructs a green bi-level risk budgeting model based on ESG integration.The upper level estimates the risk budgeting parameters,while the lower level determines the portfolio weights,thereby achieving a comprehensive optimization of expected returns,portfolio risk,and ESG benefits.Using the constituent stocks of the CSI 300 Index from 2019 to 2023 as the sample,we conduct statistical tests on the effectiveness of the model and algorithm.The empirical results show that the bi-level risk budgeting model outperforms traditional methods in both dynamic and static financial performance.This study enriches the research on risk-driven ESG asset allocation and portfolio construction,provides theoretical and algorithmic support for green investment,and offers a reference for promoting the ESG concept to better serve the low-carbon economic transition.
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.
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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: 236 ] [Citations: 0 ] [Reads: 18 ] 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.
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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.
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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.
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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: 181 ] 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: 24,234 ] [Citations: 1,023 ] [Reads: 131 ] 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: 186 ] 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: 14,419 ] [Citations: 605 ] [Reads: 147 ] 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: 181 ] 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: 186 ] 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: 24,234 ] [Citations: 1,023 ] [Reads: 131 ] 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: 15,070 ] [Citations: 492 ] [Reads: 351 ] HTML PDF Cite this article
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