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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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Estimation of the Average Treatment Effect Based on a Continuous Instrumental Variable
PAN Zhewen;The marginal treatment effect(MTE)model is an important tool for analyzing heterogeneous causal effects and an important complement to the local average treatment effect model.The MTE model postulates the existence of an instrumental variable(IV)that is continuously distributed.With the aid of the continuous IV,the MTE model can accommodate the treatment variable endogeneity and the treatment effect heterogeneity simultaneously.In addition,the MTE model has advantages such as rich in economic implications,able to identify the global rather than local average treatment effect(ATE),and so on.Based on the MTE model,identifying conditions for the global ATE are developed.The key condition is that the propensity score has a full support,or more generally,that the support of the propensity score contains the points of zero and one.Under the identifying conditions,the point identification of ATE is proved.Based on the identification result,a novel semiparametric trimmed weighted average estimator(TWAE)for ATE is suggested.Compared with the unweighted or untrimmed weighted average estimator,TWAE has finite variance and thus retains the possibility of convergence at a root-n rate,where n is the number of the sample size.The rate of convergence of TWAE is established in a general case.Moreover,two concrete examples are given to investigate the specific rates of convergence in different situations.Generally speaking,TWAE achieves root-n consistency when the distribution tail of the continuous IV is heavy relative to the distribution tail of the treatment error.A Monte Carlo simulation study demonstrates the theoretical results.Lastly,an empirical application to evaluating the return to compulsory education is provided to illustrate the usefulness of the proposed method.The construction of IV relies on the 1986 Compulsory Education Law(CEL)in China,which is a mandatory government intervention aimed at improving the completion rate of compulsory education.The existing literature usually defines the IV as the exposure intensity of CEL,which use only the variation across cohorts differentially exposed to the CEL due to differences in the timing of implementation across different provinces in China.To construct a continuous IV,the local enforcement strength of CEL is combined with the exposure intensity of CEL.Specifically,the continuous IV is defined as a weighted measure of the intensity of exposure to the CEL,where the weights are based on the geographic distance between the centroids of the home county and the corresponding provincial capital city.By this IV,the wage return to compulsory education is estimated to be0.561 2,which indicates that workers who completed the compulsory education get 56.12% higher wages on average than those who didn't,which is consistent with the existing results.In summary,the findings add theoretical supports to the applicability of the MTE model,and provide a theoretical basis for further investigating large sample properties of the MTE-based estimation of ATE.
Unified National Market Construction,Regional Division and New Quality Productive Forces Development
HUANG Manyu;WANG Haoyang;YANG Lu;Accelerating the development of new quality productive forces is essential for China to achieve high-quality economic growth and to build new advantages in international competition.It also constitutes a key pathway for advancing Chinese modernization.As a major structural reform in the domain of production relations,the unified national market provides an internal driving force for the sustained development of new quality productive forces.Given China's vast territory and pronounced regional disparities,the development of new quality productive forces requires each region to formulate strategies based on local conditions and to promote a complementary regional division that harnesses comparative advantages.Therefore,at this critical stage of transitioning from old to new growth drivers,it is essential to examine the relationship between the unified national market and new quality productive forces from the perspective of regional division.Based on the core concept of new quality productive forces,this study develops a comprehensive evaluation system encompassing laborers,objects of labor,and means of labor to measure the level of new quality productive forces in Chinese cities from 2011 to 2022.Drawing on the perspective of regional division,the analysis further examines how the construction of the unified national market influences the development of new quality productive forces.The findings are as follows:first,during the study period,the overall level of new quality productive forces in China increased steadily,but inter-city disparities widened.Second,the construction of the unified national market significantly promotes the development of new quality productive forces,and this effect remains robust after accounting for endogeneity and conducting a series of robustness tests.Third,heterogeneity analysis based on regional characteristics,government attention,and pilot policies shows that the driving effect is stronger in eastern region,during periods of heightened governmental focus,and in cities designated as free trade zones.Fourth,mechanism analysis indicates that the unified national market strengthens regional division,thereby promoting the development of new quality productive forces.This effect primarily operates through improved technological specialization,while technological diversification has not yet played a significant role at the current stage.This study offers the following policy implications.First,accelerate the development of a unified national market by improving institutional frameworks and enhancing intercity cooperation.Second,promote a complementary pattern of technological division by encouraging cities to specialize based on their comparative advantages,while enhancing inter-regional innovation networks to balance technological specialization and diversity.Third,implement differentiated regional development strategies to foster new productive forces by aligning industrial upgrading with local conditions.
Research on the Impact of Artificial Intelligence on Employee Income and Employment
SHI Guodong;DONG Ailin;HU Guoheng;WU Guo;As large language model technology reshapes human-computer collaboration patterns,is artificial intelligence(AI)an engine accelerating the growth of labor income or a catalyst disrupting employment structures?Based on data from A-share listed companies in Shanghai and Shenzhen between2009 and 2023,and leveraging the widespread adoption of large language models in 2021,this study employs a difference-in-differences(DID)model for empirical research.The results indicate that the level of AI application in enterprises has a significantly positive effect on labor income,with corporate digital transformation serving as an important channel for this effect.Heterogeneity analysis reveals that the promotive effect of AI is stronger in eastern regions than in western regions;non-heavily polluting industries experience greater benefits in labor income;high-tech and non-asset-intensive industries exhibit stronger adaptability to AI;and the effects are significant in both labor-intensive and non-labor-intensive industries.However,under high AI application levels,significance is maintained in both types of industries,whereas under low AI levels,neither shows significance.Further analysis shows that AI significantly drives overall enterprise employment growth,particularly in enterprises with high AI application levels.This study provides empirical evidence for corporate decision-making in human resource allocation and technological innovation from the perspectives of employee income and employment.Policy recommendations are proposed,including focusing on enterprise AI application levels,implementing tiered incentives,strengthening leadership in advantaged industries,promoting regional coordinated development,deepening innovation-integration and employment support,and advancing the implementation of AI technology to foster labor income growth.
The Construction of Computing Power Infrastructure and Development of Enterprise Artificial Intelligence Technology
WANG Hua;GONG Yukai;Artificial intelligence is an important national strategy.Computing power infrastructure serves as the crucial “computing foundation” for the development of artificial intelligence technology,providing massive computing resources to support modules such as large-scale parallel computing of algorithms,algorithm model training,and model operation services,thereby promoting the rapid development of artificial intelligence technology.However,upon reviewing the existing literature,it is found that there are several challenges in the development of artificial intelligence technology,such as pressure on capital investment,lack of human capital,and insufficient technical foundation.Therefore,whether the construction of computing power infrastructure will solve these problems and thereby promote the development of artificial intelligence technology in enterprises is worthy of in-depth study.Based on this,this study takes the listed companies in Shanghai and Shenzhen stock markets from 2010 to 2023 as the research sample,and employs the least squares method(OLS)to conduct an empirical test to examine whether the construction of computing power infrastructure can promote the development of artificial intelligence technology in enterprises and the mechanism of its effect.The result shows that the construction of computing power infrastructure significantly promotes the development of enterprise artificial intelligence technology.The mechanism analysis shows that the construction of computing power infrastructure plays a promoting role by easing the pressure of capital investment,improving the level of human capital and enhancing the capability of digital technology.The heterogeneity analysis shows that the promotion effect is more significant in small and medium-sized enterprises and non-technical board companies.Industry heterogeneity analysis shows that the promotion effect is more significant in manufacturing,technology-intensive and capital-intensive industries.Regional heterogeneity analysis shows that the promotion effect is more significant in the areas with low financial development,low educational resources and high computing power application.Based on the research results,suggestions are proposed from both the government perspective and the enterprise perspective.The policy suggestions from the government perspective include enhancing the regional computing power supply level and the level of computing power application inclusiveness,implementing fiscal policies such as government subsidies and tax incentives,planning regional higher education reforms,increasing the intensity of talent recruitment,supporting the aggregation of digital industries,etc.The development suggestions from the enterprise perspective include actively connecting and integrating computing resources,optimizing production and operation,accumulating relevant technical talents,strengthening digital technology capabilities,etc.
Research on the Income-enhancing Effects and Mechanisms of the Rural Collective Property Rights System Reform for Farmers
ZHOU Yusong;LAN Yongsheng;WANG Yan;The reform of the rural collective property rights system,as a landmark innovation in China's top-level institutional design for its new rural governance concept,plays a crucial role in safeguarding the income rights and interests of farmers' collective assets and promoting sustainable growth in farmers' income.Constructing aquasi-natural experiment based on the phased rollout of pilot projects for the rural collective property rights system reform since 2015.Using panel data from 1,482 counties in China spanning the period from 2010 to 2023,a multi-time-period difference-in-differences model is established to systematically evaluate the income growth effect of the rural collective property rights system reform on farmers and explore its underlying mechanisms.The findings reveal that the reform has significantly boosted farmers' income growth,with this policy effect being more pronounced in pilot counties located in central and western regions,those with favorable financing environments,and those with larger populations.Mechanism analyses indicate that attracting capital inflows into pilot counties and facilitating the outward migration of surplus labor are the primary channels through which the rural collective property rights system reform enhances farmers' income growth.Based on these conclusions,the study proposes targeted recommendations,including optimizing the design of the rural collective property rights system,dismantling institutional barriers that restrict the free flow of factors,and clarifying key directions for future government policies.These suggestions aim to provide new theoretical insights and empirical support for consolidating the achievements of the rural collective property rights system reform and ensuring stable increases in farmers' income.
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 paper 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.The research in this paper 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 micro-enterprises,which has important theoretical and practical significance.
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Extremal Dependence-based Climate Risk Regionalization and Derivative Portfolio Construction
MENG Shengwang;MA Ning;As global climate change intensifies,catastrophic climate risks pose a significant threat to socio-economic stability,particularly in geographically diverse and vulnerable countries like China.To address this challenge,the Chinese Actuaries Climate Index(CACI) is construted as a standardized,multidimensional metric that provides a quantitative measurement of regional climate risks at the prefecturelevel city scale using historical data on temperature,precipitation,drought,and wind speed.Existing research has largely relied on methods that overlook the spatial tail dependence structure of extreme events,which exacerbates systemic risk and limits the effectiveness of regional risk management.A novel climate risk regionalization method based on multivariate extreme value theory is proposed to fill this critical gap.The primary objective of this study is to model the tail dependence of climate risks across Chinese cities and apply this structure to optimize climate derivative portfolios,thereby providing a new,robust tool for managing systemic climate risk.The methodology employs an extremal graphical model,where cities are represented as nodes and their risk dependencies are represented as edges,to analyze the inter-regional dependencies of catastrophic climate risks.A novel EMTP2(Extremal Multivariate Total Positivity of order two) constraint and a spatial constraint are introduced to regularize the graph structure,ensuring a sparse,interpretable model focused on positive dependence.Spectral clustering is then applied to a composite similarity matrix,which innovatively combines both the extremal dependence and spatial information,to generate climate risk zones that account for both risk dependence and geographical consistency.To test the practical application of these zones,climate index options are constructed for each city whose payoffs are tied to the CACI.Empirical results validate the effectiveness of the methodology.The efficacy of the EMTP2 constraint in identifying conditional extremal independence is confirmed by comparing the model' s parameter matrices before and after its application.Furthermore, an evaluation of different spatial constraint matrices reveals that a matrix derived from moderate relaxation of the spatial adjacency matrix yields the best clustering performance.This finding indicates a pronounced spatial agglomeration effect of climate catastrophe risks,meaning high-risk areas are often geographically clustered.In the application part,analyzing the efficient frontiers of option portfolios demonstrates the effectiveness of spatial diversification.A portfolio strategically diversified across different risk zones achieves a superior risk-adjusted return on capital of 16.93 %, substantially outperforming a portfolio concentrated within a single,highly dependent zone(8.86 %),which is attributable to the low correlation of extreme events between the selected zones.In conclusion,a robust, dual-contribution framework is introduced,featuring both a novel climate index and a sophisticated risk zoning methodology.The findings underscore the critical importance of spatial diversification strategies,informed by tail dependence structures, in mitigating systemic risk and enhancing portfolio stability.Significant practical implications are offered not only for the pricing of insurance products and the strategic allocation of climate derivative portfolios,but also for guiding governmental disaster-preparedness planning and resilient infrastructure investment.
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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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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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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: 39,911 ] [Citations: 1,960 ] [Reads: 91 ] 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: 22,327 ] [Citations: 584 ] [Reads: 67 ] 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: 25,942 ] [Citations: 542 ] [Reads: 104 ] HTML PDF Cite this article
A Review of Technologies on Quantile Regression
CHEN Jian-bao,DING Jun-jun(Macroeconomics Research Center,Xiamen University,Xiamen 361005,Fujian)Ordinary least square(OLS) regression models the relationship between vector of covariate and the conditional mean of a responsegiven.However,quantile regression models the relationship between covariateand the conditional quantiles of given.Taken together the ensemble of estimated conditional quantile offers a much more complete view of the effect of covariates on the location,scale and shape of the distribution of the response variable.It is especially useful in applications where people are interested in upper or lower quantiles of a response.In this paper we first introduce the concept of quantile regression,then provide some brief methods about estimation,hypothesis tests and goodness-of-fit of quantile regression,some important aspects of applications in economics are reviewed,a summary is given in the final section.
[Downloads: 9,970 ] [Citations: 409 ] [Reads: 112 ] HTML PDF Cite this article
A Review of Technologies on Random Forests
FANG Kuang-nana,b,WU Jian-bina,ZHU Jian-pinga,b,SHIA Bang-changa,b(a.Department of Statistics,School of Economics;b.Data Mining Center,Xiamen University,Xiamen 361005,China)Random Forests is a statistical learning theory,using bootsrap re-sampling method form sample sets,and then combining the tree predictors by majority voting so that each tree is grown using a new bootstrap training set.It is widely applied in medicine,bioinformatics,economics and other fields,because of its high prediction accuracy,good tolerance of noisy data,and the law of large numbers they do not overfit.In this paper we first introduce the concept of random forest and the latest research,then provide some important aspects of applications in economics,and a summary is given in the final section.
[Downloads: 39,911 ] [Citations: 1,960 ] [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: 25,942 ] [Citations: 542 ] [Reads: 104 ] 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: 22,327 ] [Citations: 584 ] [Reads: 67 ] HTML PDF Cite this article
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