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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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Statistics Accounting of Digital Products
ZHANG Meihui;GUO Meiting;XU Xianchun;With the rapid advancement of digital technology,the variety of digital products has expanded significantly,playing a vital role in promoting economic and social development.Research on the statistical classification and accounting treatment of digital products is essential for compiling Supply-Use Tables for the Digital Economy(Digital SUTs),improving the digital economy's statistical measurement system,and accurately reflecting the impact of digital products on economic and social development.Firstly,a review is carried out of the development history from “ICT products” to “content and media products” and further to “digital products”.With reference to the latest international standard for national accounting,the System of National Accounts 2025(SNA 2025),the definitions and classifications of digital products are elaborated,and their key characteristics sorted out,including non-rivalry,network effects,rapid iteration,and spatial transcendence.Secondly,it summarizes the important role of digital product statistical accounting in the measurement of macroeconomic statistical indicators,the monitoring of the development level of digital economy and the improvement of enterprise production efficiency and market adaptability.Thirdly,international and domestic research progress on specific types of digital products such as cloud computing,data and databases,artificial intelligence,free digital products,and non-fungible tokens is systematically reviewed.By aligning digital products with the officially issued Statistical Classification Catalogue of Products in China,this study attempts to identify relevant product categories that correspond to or are widely penetrated by digital products,and further explores appropriate valuation methods.Finally,the challenges and future directions for the statistical accounting of digital products are outlined,with corresponding policies and suggestions proposed.A reference is provided for improving the statistical accounting system of digital products and the digital economy,and theoretical and methodological support is offered for promoting the high-quality development of the digital economy.
The Impact of Data Factor Marketization on the Resilience of Manufacturing Supply Chain
LI Yan;CHEN Guodong;WANG Peng;Advancing data factor marketization can fully unlock its value,crucially enhancing manufacturing supply chain resilience.Based on data of A-share manufacturing listed companies from 2011 to 2021,this study systematically examines the impact mechanisms and effects of data factor marketization on supply chain resilience through dual perspectives of market operations and policy guidance.The results show that data factor marketization significantly strengthens supply chain resilience,and this conclusion remains robust across a series of robustness tests.From the market perspective,the effect is more pronounced for firms with lower market positions,non-stateowned enterprises,and firms in technologyintensive industries,highlighting the inclusiveness and technological attributes of data factor marketization.Mechanism analysis shows that,at the firm level,data factor marketization enhances manufacturing supply chain resilience by reducing transaction costs and facilitating digital transformation.From the policy perspective,at the city level,the establishment of data trading platforms improves manufacturing supply chain resilience by stimulating digital innovation.Moreover,stronger regional intellectual property protection further strengthens the positive effect of data factor marketization on manufacturing supply chain resilience.These findings provide important policy implications for realizing the potential value of data factors and synergistically enhancing manufacturing supply chain resilience through the coordinated roles of market mechanisms and policy guidance.
Research on the Mechanism and Effect of Data Elements Driving Corporate Green Transformation
SUN Panfeng;ZHUO Ronghai;TIAN Maozai;Green development refers economic growth and social development that aims at efficiency,harmony and sustainability,with its core being the achievement of harmonious coexistence between environmental protection and economic development,thereby realizing a win-win outcome.Currently,Chinese enterprises still face two major challenges in their green transformation proess:insuffieient transformation momentum and inadequate transformation 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 corporate green transformation?Does significant heterogeneity exist in this driving effect?Answering the above questions is not only crucial for enterprises to innovate their production and operation methods and advance their green,high-quality and sustainable development,but also of great significance for promoting China's economic transition to green development,achieving the“Dual Carbon” goals,and realizing high-quality and sustainable economic development.Therefore,this study addresses the above issues through theoretical analysis and empirical verification.This paper selects all A-share non-financial listed companies in China from 2011 to 2023 as the research samples,and employs a two-way fixed-effects regression model,to empirically examine the impact of micro data elements on corporate green transformation in China and its underlying mechanisms from a micro-level perspective.The study finds that:First,data elements can effectively drive the green transformation of Chinese enterprises.Second,data elements can effectively alleviate the information asymmetry faced by enterprises,promote green technological innovation,and thereby drive corporate green transformation.Third,government subsidies play apositive moderating role in the process of data-driven corporate green transformation.Moreover,the driving effect of data elements on corporate 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 above findings,this study constructs a systematic solution from the three dimensions:institutional innovation,subject empowerment,and policy synergy,to provide a multi-dimensional practical path for fully releasing the multiplier effect of data elements in green transformation.This study not only provides theoretical insights and practical decision-making reference for corporate green transformation in the digital economy era,but also aligns with the requirements of the “dual carbon” strategy and highquality development.It further provides a way to crack the structural contradiction in the “transition pain period”,and supports China in building a modernized industrial system and a green development model.
Spatiotemporal Evolution and Influencing Factors of the Coupling Coordination between New Quality Productive Forces and Economic Resilience in China
ZHU Baoji;HOU Renyong;ZHANG Quan;Clarifying the interplay between new quality productive forces and economic resilience,and capturing their coupling coordination dynamics,is essential for promoting the development of new quality productive forces and advancing China's high-quality economic growth.Based on an integrated evaluation framework,a coupling coordination degree model,kernel density estimation,spatial correlation analysis,and spatial econometric models are employed to examine the spatiotemporal evolution and determinants of their coupling coordination degree in China from 2014 to 2023.Results show that:both systems exhibit steady upward trends,while the coupling coordination degree evolves toward a bipolar pattern,with increasing regional dispersion and widening absolute disparities;Spatial heterogeneity is observed,characterized by a“high in the east and low in the west” pattern,with stable spatial dependence reflected in “H-H” clusters in the eastern coastal region centered on the Yangtze River Delta and “L-L” clusters in the western and northeastern regions centered on Inner Mongolia,Xinjiang,and Jilin;A significant mutually reinforcing effect exists between the two systems,with new quality productive forces exerting a stronger positive impact.Specifically,new quality productive forces contribute most to the transformation and development capability subsystem,while economic resilience has the strongest marginal effect on the new quality meansof-labor subsystem.Furthermore,virtual agglomeration,government intervention,urban economic development,market scale,and teaching and research significantly enhance local coupling coordination,whereas foreign direct investment exerts an inhibitory effect.Government intervention,market scale,and education and research produce positive spatial spillovers,whereas virtual agglomeration and foreign direct investment generate negative spatial spillovers.
Spillover Effect of Local Government Debt: Based on the Perspective of Real Estate Enterprise Leverage Ratio
WU Yidong;ZHAO Jinping;WANG Xianzhu;Local debt risks and real estate risks represent two critical areas in the prevention of systemic financial risks.Addressing these risks in a steady and orderly manner is essential for safeguarding financial stability and fostering high-quality development.Based on hand-collected comprehensive data on local government debt,this study employs a panel fixed-effects model at the firm level to empirically examine how local government debt affects the leverage ratio of listed real estate enterprises.The findings reveal that whether local government debt leads to higher leverage in real estate firms depends on the region's reliance on land finance.In areas with high land finance dependency,local government debt significantly increases the leverage of listed real estate companies.This effect is particularly pronounced in regions with lower levels of economic development,greater fiscal pressure,and weaker market institutions,as well as for real estate firms with abundant internal financing and slower accounts payable turnover.Further analysis indicates that local governments primarily transfer debt pressure to real estate enterprises through the land scale-price effect and the credit constraint alleviation effect,which drive up short-term leverage and encourage inventory accumulation.However,when credit policies for the real estate sector are tightened,the risk transmission channel from local government debt to the real estate sector is disrupted,resulting in a “debt dam” phenomenon.Accordingly,this paper proposes that fiscal and tax system reforms should be deepened to enhance the sustainability of local public finances,steadily and orderly weaken the risk linkage between local government debt and the real estate sector,and accelerate the establishment of a new model for real estate development.
Research on Interval Time Series Forecasting for Addressing Information Redundancy and Pseudo-interval Issues
WANG Piao;TAO Zhifu;LIU Jinpei;Compared with traditional point data,interval data can depict the dynamic change process of data more completely,and has important application value in fields like economic forecasting and environmental monitoring.However,existing interval data forecasting methods generally have two core problems:first, they fail to fully utilize the inherent similarity of upper and lower bound information of intervals, leading to information redundancy;second,forecasting results are prone to "pseudo-intervals"(with reversed upper and lower bounds), which seriously impair forecasting effectiveness.Based on this,a new interval time series forecasting method is proposed integrating PC A dimensionality reduction and reconstruction.In the research process, first, PC A is used to convert interval data into a one-dimensional time series, which retains over 95 % of key information of the original data and effectively solves the information redundancy problem.Second, under the assumption that the original data distribution remains stable,common forecasting methods are adopted to predict the dimensionally reduced series,and PC A inverse transformation is applied to realize interval reconstruction,which fundamentally avoids pseudointerval generation.Finally,for multivariate scenarios,it completes modeling through one-time information integration,significantly reducing error accumulation caused by repeated data use.Meanwhile,Pseudointerval Rate(PIR),Prediction Interval Coverage Probability(PICP) and Mean Normalized Prediction Interval Width(MNPIW) are introduced to construct a multi-dimensional evaluation system for comprehensively measuring forecasting performance.Empirical results and analysis show that while solving information redundancy and pseudo-interval problems,it significantly improves the forecasting accuracy of interval time series,provides a new idea with both theoretical innovation and practical feasibility for interval time series forecasting research,and offers more reliable technical support for decision-making based on interval data in related fields.
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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 if they lack independent legal personality.This study focuses on how China's " Business Tax to Value-Added Tax Reform "(B2 V 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 B2 V 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 paper applies a three-dimensional time-based analytical framework to empirically assess the impact of the B2 V Reform on the accuracy of industry classification data and to examine variations across sectors.Exploratory adjustments are also made to relevant historical data.The 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 adj ustment, employment figures in these two corrected sectors-based on urban nonprivate units-exceed the originally reported values.This outcome confirms that the B2 V Reform helps mitigate the underestimation of historical data in related service industries.Overall,this study validates the role of the B2 V 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.
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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.
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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.
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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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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: 48,178 ] [Citations: 2,541 ] [Reads: 112 ] 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: 23,688 ] [Citations: 823 ] [Reads: 91 ] 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: 28,754 ] [Citations: 676 ] [Reads: 129 ] 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.
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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: 48,178 ] [Citations: 2,541 ] [Reads: 112 ] 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: 28,754 ] [Citations: 676 ] [Reads: 129 ] 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: 23,688 ] [Citations: 823 ] [Reads: 91 ] 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.
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