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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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Modal Regression Estimation of Panel Data Models with Time Trends
CHENG Yao;HAN Zhongcheng;YAN Shuting;LIN Jinguan;Most empirical and theoretical studies on panel data rely on least-squares loss or quantile-type loss functions.Although widely used,these approaches may lack robustness and efficiency when the underlying data distribution exhibits substantial skewness or heavy-tailed behavior.Modal regression offers an attractive alternative because it provides shorter predictive intervals and is less sensitive to asymmetric or contaminated distributions.However,conventional fixed-effects modal regression models typically ignore time-specific effects,which are essential for capturing common temporal dynamics of the dependent variable.Neglecting these effects implies that important time-varying patterns may be missed.Moreover,cross-sectional dependence among observational units is often unavoidable in panel-data settings,increasing the complexity of model estimation.To overcome these limitations,this study incorporates modal regression into a fixed-effects framework by introducing an explicit time-trend component,enabling simultaneous modeling of individual heterogeneity and shared temporal evolution.The proposed model is flexible and nests several known forms:if coefficients vary over time,it reduces to a time-varying coefficient nonparametric fixed-effects panel model;if coefficients vary with an index,it becomes a fixed-effects functional-coefficient panel model with a trend;if coefficients vary only across individuals,it coincides with a traditional varying-coefficient panel model;and when the trend is omitted,it simplifies to the standard fixed-effects modal regression model.The trend component is approximated using B-spline basis functions,and parameters are estimated via an improved expectation-maximization(MEM)algorithm,maximizing the modal-regression objective function.The iterative scheme involves weighted least-squares updates with non-decreasing objective values,ensuring stable convergence.Under standard regularity conditions,the asymptotic properties of the estimators are established,including consistency of regression coefficients,fixed-effects,and the time-trend component.Regression coefficients are asymptotically normal,allowing confidence intervals to be constructed.Monte Carlo simulation results indicate that all models perform accurately in small samples,while bias and root mean squared error decrease as the time dimension grows.Across distributions,the model with a time trend achieves the smallest root mean squared errors and exhibits more stable performance.Minor increases in bias occur rarely and are negligible,confirming robustness under skewed or irregular distributions.Furthly,using provincial-level panel data from China spanning 2012—2021,the proposed model is applied to examine the dynamic relationship between foreign direct investment(FDI) and economic growth.After controlling for distributional skewness,the trend-augmented modal regression model delivers superior goodness-of-fit results,as reflected by higher coefficient of determination and lower BIC values relative to both the notrend modal model and the least-squares fixed-effects model.These findings demonstrate stronger robustness,improved variable-selection capability,and higher estimation accuracy.The study extends the theoretical framework of modal regression and offers a robust tool for analyzing panel data with temporal trends.Future research may address bandwidth selection and random-effects panel models.
Quantitative Policy Analysis and Implementation Effect Evaluation of Data Elements Driving Strategic Emerging Industries Development
LI Jinchang;ZHAO Zeyu;XIANG Ying;Giving full play to the fundamental resource role and innovation engine function of data elements to drive the high-quality development of strategic emerging industries is an inevitable requirement for accelerating the construction of Chinese modernization.This study follows a "from macro to micro" research logic to conduct a quantitative analysis of policies and an evaluation of implementation effects concerning data elements driving the development of strategic emerging industries.Utilizing the CogLTX long-text dynamic segmentation technology integrated with the BERTopic deep semantic modeling method,an in-depth mining and feature analysis is performed on 623 policy texts related to data elements driving strategic emerging industries from 2010 to 2024.On this basis,taking the core thematic module of "infrastructure support" as a typical case and further focusing on the "Broadband China" policy,the multiperiod difference-in-differences method is employed to empirically measure the impact of this policy on the structural upgrading of China's strategic emerging industries.The research findings indicate that:(1)During the sample period,policy themes for driving strategic emerging industries through data elements focuse on five major areas: "infrastructure support,industrial upgrading,market reform,technological breakthroughs,and financial assistance" demonstrating a three-stage policy evolution trend of "strategic deployment,supportive development,and coordinated integration".(2) The implementation of digital infrastructure support policies has a significant positive impact on the structural upgrading of strategic emerging industries.(3) Heterogeneity analysis and mechanism tests reveal that the positive impact of digital infrastructure support on the structural upgrading of strategic emerging industries is more pronounced in private enterprises,growth-stage enterprises,and the central and western regions.(4)Digital infrastructure support promotes the structural upgrading of strategic emerging industries by enhancing supply chain stability and reducing resource misallocation.Based on these conclusions,this study proposes policy recommendations centered on establishing a clear delineation of rights and responsibilities,implementing differentiated support strategies tailored to regional and firm-specific conditions,and harnessing data elements to enhance supply chain stability and optimize resource allocation.
Research on the Enabling Effect of Platform Economy on Enterprise Value Based on Large Language Model
GUO Lu;YUAN Yingqian;WANG Zhenghai;In the era of digital economy,with the rapid development of information technology,platform economy has become a new engine of economic growth.It is urgent for enterprises to deeply integrate the development of platform economy with the improvement of their own value to lay a solid foundation for their long-term development.In order to deeply explore the impact of platform economy on enterprise value and explore its mechanism,this study uses ERNIE grand language model and enterprise annual report to accurately identify the development of enterprise-level platform economy.On this basis,relevant data of China's A-share listed enterprises from 2013 to 2022 are used as samples to conduct empirical research.It is found that the development of platform economy significantly drives the improvement of enterprise value,and this conclusion is still valid after a series of robustness tests.Further mechanism analysis shows that on the one hand,the development of platform economy can drive the rise of enterprise value by improving enterprise innovation efficiency;On the other hand,it can promote the improvement of enterprise value by improving the total factor productivity of enterprises.This effect is more obvious in high-tech enterprises,non-labor-intensive enterprises and enterprises in the western region.This study provides empirical reference and policy enlightenment for in-depth understanding of the driving effect of platform economy development on enterprise value and promoting the deep integration of Digital platform and microenterprises,which has important theoretical and practical significance.
Digital Innovation Empowering High-quality Industrial Development:the Lens of New Quality Productive Forces
WANG Lijun;LIU Qiang;XU Shengxia;Digital innovation that empowers high-quality industrial development constitutes a critical pillar for accomplishing the task of high-quality economic growth in the new stage,with the unleashing of new quality productive forces playing a central role.An index system for high-quality industrial development is constructed along two dimensions,industrial structure upgrading and the green low-carbon transition.Using provincial panel data for China from 2011 to 2022 and a structural-equation-based multiple mediation framework,the impacts of digital innovation on high-quality industrial development and the underlying mechanisms are empirically examined.Four main findings are obtained.First,digital innovation significantly enhances high-quality industrial development,and the effect exhibits a progressively increasing nonlinear pattern.The conclusion remains robust after multiple robustness checks and validation using a random forest model.By dimension,the promoting effect on industrial structure upgrading strengthens in a stage-wise manner,while the effect on the green low-carbon transition follows a U-shaped pattern,with initial inhibition followed by promotion.Second,mechanism analyses indicate that digital innovation empowers high-quality industrial development through two channels.One channel operates directly through systematic upgrading of traditional labor,instruments of labor,and objects of labor,thereby generating new quality productive forces and accelerating the transition of industries toward a high-quality stage.The other channel operates through a chain pathway in which digital innovation fosters new-type workers,which in turn drives innovation and adoption of new-type instruments of labor,thereby indirectly releasing new quality productive forces.A comparison of pathway effects shows that the most effective route is the one in which digital innovation directly transforms new-type objects of labor and thereby promotes high-quality industrial development,whereas the chain pathway in which new-type workers influence new-type objects of labor contributes relatively less.Third,both regional intellectual property protection and environmental regulation moderate the empowering effect of digital innovation on high-quality industrial development.Stronger intellectual property protection amplifies this moderating role,while excessively stringent environmental regulation weakens the positive moderation.In addition,moderate environmental regulation strengthens the empowering effect,but the positive moderation diminishes when regulation becomes highly stringent.Fourth,heterogeneity analyses show that digital innovation significantly promotes high-quality industrial development in the eastern and western regions,with a stronger effect in the east,while the effect is insignificant in the central region.In areas with a stronger industrial base,digital innovation exerts a significant positive impact,supporting the cumulative advantage of innovation-driven development.In areas with a weaker industrial base,the positive effect has not yet materialized and instead appears negative.These findings reveal a dynamic trade-off between efficiency and sustainability during high-quality development providing theoretical support for a stepwise transition path from "efficiency first" to "green catch-up".The evidence also helps clarify the direction and pathways of high-quality industrial development and offers empirical support for building a modern industrial system.
Analysis of the Impact of New Quality Productive Forces on Industrial Structure Upgrading
ZHANG Tonglei;MA Yuan;With the accelerated evolution of the new round of scientific and technological revolution and industrial change,the new quality productive forces,as a contemporary advanced productivity,has become a powerful support to promote the upgrading of China's industrial structure.Based on the data at the level of 285 prefecture-level cities in China from 2010 to 2022,the effect of the development of new quality productive forces on the upgrading of industrial structure is explored,and tries to analyze the mechanism of action from the supply side and the demand side.It is found that the new quality productive forces can significantly promote the upgrading of China's industrial structure,and this conclusion is validated by the robustness of multiple conventional and reset dual machine learning models.The mechanism test shows that NQP can optimize supply by improving total factor productivity on the supply side,boost demand by promoting consumption upgrading on the demand side,and synergize supply and demand through fintech,and then promote the upgrading of the industrial structure.The heterogeneity test shows that the positive impact of NQP on industrial structure upgrading is significantly higher in the case of central and western regions,low levels of industrial structure upgrading,laborers,labor objects,means of production,financial decentralization,market potential,and resource endowment.It is indicated that the pace of industrial structure upgrading can only be accelerated by advancing innovation-driven institutional mechanism reform,optimizing the allocation of new-quality factors of production,vigorously developing advanced manufacturing industries,enhancing industrial competitiveness driven by scientific and technological innovation,and focusing on the upgrading paths of supply and demand on both sides and the heterogeneity of various conditions.
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.
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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.
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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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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.
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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.
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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.
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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: 47,692 ] [Citations: 2,514 ] [Reads: 101 ] 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: 28,613 ] [Citations: 672 ] [Reads: 117 ] 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: 23,418 ] [Citations: 770 ] [Reads: 79 ] 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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