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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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Non-probability Sample Inference Based on Random Forests with Stratified Weighting
YANG Jingbo;ZHOU Qi;Due to the uncontrollable nature of selection mechanisms,non-probability samples suffer from serious selection bias problems,which limit their application in population inference.Traditional non-probability sample inference methods mainly depend on the correct specification of parametric models,and large estimation bias is produced when model misspecification occurs.Although non-parametric methods such as kernel methods and k-nearest neighbors alleviate the model specification problem to some extent,they often perform poorly when high-dimensional auxiliary variables are involved.To address this problem,a random-forest-based stratified weighting inference method for non-probability samples is proposed.First,weighted CART classification trees are constructed to identify the selection mechanism and to classify homogeneous units.Then,drawing on the idea of stratified sampling,the non-probability sample is used to estimate the mean of the target variable within each leaf node,the probability sample is used to estimate the scale weight of each leaf node,and the population mean is estimated from a single tree.Finally,estimation accuracy and robustness are improved through the random forest ensemble.In addition,variance estimation of the estimator is provided based on the traditional infinitesimal jackknife method.Simulation studies show that,compared with the k-nearest-neighbor-based estimation method,the proposed method can effectively identify the selection mechanism when the dimension of auxiliary variables is high,and the estimator is more robust and efficient.The proposed method is applied to non-probability samples collected by the Pew Research Center to estimate two indicators concerning American public attitudes toward national conditions and interpersonal relationships.
Patient Capital Shareholding and Corporate High-quality Innovation: Evidence from the Perspective of Innovation Breakthrough
WU Wenwu;WANG Yu;BA Wenhao;DU Guozi;The development of breakthrough,disruptive,and original high-quality innovation represents an essential pathway for Chinese enterprises to overcome technological bottlenecks and achieve high-quality development.Based on an innovation breakthrough index,this study measures the level of high-quality innovation among A-share listed firms in the Shanghai and Shenzhen stock exchanges from 2008 to 2019.Drawing on resource dependence theory,it further examines the impact of patient capital ownership on firms' high-quality innovation.These findings indicate that patient capital ownership significantly promotes high-quality innovation.Mechanism analyses show that this effect is primarily realized through the mitigation of managerial short-termism,the alleviation of financing constraints,and the upgrading of the human capital structure.Heterogeneity analyses further reveal that the promoting effect of patient capital ownership is more pronounced in firms operating in highly competitive industries,in regions with stronger intellectual property protection,among small-sized enterprises,and in samples involving corporate venture capital.These findings uncover the specific effects and underlying mechanisms through which patient capital ownership supports the development of high-quality innovation,and provide valuable insights for fostering and strengthening patient capital,as well as for building a capital support system conducive to high-quality innovation in China.Firms should proactively explore effective approaches to attract patient capital into their ownership structures and cultivate governance environments that enable it to play a full role.Meanwhile,the government should continue to improve the institutional framework for long-term capital investment,strengthen policy guidance and institutional support,reduce the uncertainty and institutional costs associated with long-term investment,and foster an external environment conducive to the value-creation function of patient capital.
Internet Development and Carbon Total Factor Productivity Enhancement in the Service Sector
WANG Xuliang;LI Yaqin;There are dual problems of long-term efficiency lag and growing carbon emissions in China's service sector,and there is an urgent need to improve the carbon total factor productivity(TFP) of the service industry.Accordingly,this study explores the potential drivers of carbon TFP growth in the service sector from the perspective of internet development.Firstly,this study investigates the overall impact of the internet development on carbon TFP of the service sector and the transmission mechanisms from the theoretical level.Then,the entropy method and the non-radial biennial Malmquist-Luenberger index are used to measure the internet development and the carbon TFP of the service industry,respectively,and the impact of the internet development on the carbon TFP of China's service sector is identified from the empirical level.The findings show that there is a significant positive impact of internet development on service sector carbon TFP,and the positive impact of internet development on service sector carbon TFP is mainly reflected in the later period of the sample(2013-2021) and in the eastern region.The mechanism test finds that internet development increases service sector carbon TFP by promoting low-carbon technological progress and optimizing resource allocation in the service industry.Further discussion finds that service sector marketization and human capital strengthen the positive impact of internet development on service sector carbon TFP.In addition,there is a positive spatial spillover effect of internet development on service sector carbon TFP.Accordingly,coordinated efforts in network upgrading,digital and lowcarbon technology R&D,cross-regional factor mobility,marketization,and human capital are warranted to fully unleash the potential of internet development in empowering service sector carbon TFP.
Drivers and Mechanisms of County-level Consumption in China:Evidence from Interpretable Machine Learning
ZHANG Miao;WANG Yukun;XIAO Hongce;YOU Shibing;County-level consumption serves as a crucial pillar for constructing the “dual circulation”development paradigm, and identifying its key drivers holds significant implications for promoting high-quality county economic development. Based on panel data from 2 513 counties in China spanning 2010-2023, this study constructs machine learning models including XGBoost, and compares it with traditional panel fixed-effects models, to systematically identify key factors influencing county-level consumption and their underlying mechanisms. The findings reveal that: first, the XGBoost model demonstrates superior performance in predicting county-level consumption, significantly outperforming Light GBM,Random Forest and traditional econometric models,indicating that machine learning methods can effectively capture the multi-dimensional driving mechanisms of county consumption. Second,global attribution analysis based on SHAP mean absolute values shows that tertiary industry value-added is the primary driving factor for county-level consumption, followed sequentially by the year-end resident population,per capita regional GDP,mean consumption of other counties in the same city,the number of broadband access users,and the urbanization rate as key driving factors. Furthermore,SHAP dependence plots unveil the nonlinear mechanisms and interaction effects among these factors. Specifically,there is a significant interaction between the value-added of the tertiary industry and population scale:it exhibits a pronounced positive driving effect on consumption within the low-to-medium industry value range, but shows diminishing marginal effects under the combination of high industry value and large population scale. Additionally,significant threshold effects exist for population scale and urbanization rate. Based on these findings,it is recommended to implement differentiated regulatory strategies that match industrial development with population scale to avoid blind expansion, promote the equalization of basic public services and substantive citizenship to resolve structural contradictions,and introduce digital-intelligent governance tools to build a dynamic monitoring system,thereby precisely stimulating the consumption potential of county-level lower-tier markets.
Research on Horizontal Benefit Compensation Mechanism for Grain Producing and Marketing Regions Based on the Dual Perspectives of Ecological Cost and Opportunity Cost
HAI Xiaohui;HE Jitong;ZHU Jianping;WANG Chunzhi;The horizontal benefit compensation mechanism between grain producing and marketing regions represents a significant institutional innovation for ensuring national food security and promoting regional coordinated development.First,the grain producing and marketing regions are reclassified by integrating four indicators,including grain security contribution,to construct a more scientific and rational regional classification system.Based on this,a comprehensive compensation standard is systematically established from a dual perspective of "ecological cost opportunity cost," incorporating both positive and negative values of cultivated land ecosystem services,as well as the implicit labor cost and the value of cultivated land development rights.Furthermore,a complete compensation framework is proposed,featuring a "phased and diversified" funding mechanism,an implementation pathway combining "horizontal local compensation with vertical central coordination," and a supporting safeguard system.Results show that the number of major producing regions has decreased to nine,while major marketing regions have increased to nine,reflecting a pattern of "concentrated production and dispersed consumption." The total compensation required by producing regions amounts to 10 662.90 billion CNY,while marketing regions should contribute 9 984.67 billion CNY.Heilongjiang,Jilin,and Henan rank top three in compensation receipts,whereas Guangdong,Zhejiang,and Fujian are the top three contributors.The proposed compensation framework and scheme can provide theoretical foundations and practical references for establishing a scientific and sustainable inter-regional grain compensation mechanism in China.
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 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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Study on Statistical Data Quality and Survey Compilation of Green Finance
SHI Daimin;YU Lan;SHI Haoming;Green finance serves as a critical pillar for sustainable development and the Chinese modernization.In recent years,the rapid development of green finance in China has facilitated the transformation of the economy towards a higher level and quality,while also contributing to the achievement of carbon peaking and carbon neutrality goals.In the process of rapid development of green finance,statistical theory of green finance lags behind the practice of green finance.Although statistical theory and practice have been established for green financial products such as green credit,green insurance,and green bonds,there are still many issues that need to be explored in depth regarding the classification,framework,and measurement of green finance statistics.In particular,the standards and systems for green finance statistics are relatively fragmented,and the data is still in complete and of insufficient quality,there is a lack of a comprehensive statistical system that can thoroughly monitor the development of green finance.Compiling a green finance survey can effectively present fundamental data on the total volume and structure of green finance,which facilitates a comprehensive and systematic monitoring of green financial activities and aiding in the analysis and assessment of the development status of green finance.Therefore,following the logical requirements of green finance statistical monitoring,this paper aims to compile a green finance survey.Specifically,it examines several fundamental issues,including the classification of green finance statistics,the data foundation,and the challenges in compiling the survey and the flow of funds table.The findings indicate that the current classification of green activities in statistical standards and systems is mainly based on industrial levels.To meet the diverse demands for green finance from government departments,enterprises,the general public,it is necessary to classify green finance from multiple perspectives,including the degree of greenness and its effects,and conduct multi-level green finance total amount.And it is necessary to further refine and expand the scope of green finance statistics,extending the statistical perspective from financial institutions to multiple sectors involved in green finance activities.Additionally,efforts should be made to optimize and enhance the structure and quality of green finance data,involve systematically constructing a multi-dimensional green finance database and establishing a quality supervision system for green finance.Finally,by integrating the various specialized statistical standards and systems of green finance,the compilation of a green finance survey and flow of funds table is proposed.These tools are designed to reflect the specific manifestations of green finance flows and stocks at different classification levels,providing an effective solution to the current lack of comprehensive green finance statistics.The research results are helpful to improve the statistical theory of green finance and provide some references for establishing a comprehensive statistical system of green finance.
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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: 154 ] 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: 24,162 ] [Citations: 979 ] [Reads: 122 ] 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: 170 ] 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: 48,490 ] [Citations: 2,563 ] [Reads: 154 ] 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: 170 ] 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: 24,162 ] [Citations: 979 ] [Reads: 122 ] 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: 15,031 ] [Citations: 484 ] [Reads: 343 ] HTML PDF Cite this article
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