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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 Green Employment Scale and Its Effects Analysis in China
XU Qiang;MIAO Tong;The green economy constitutes a cornerstone of national development strategy for China,with the nation currently navigating a decisive phase in its green transformation.To comprehensively evaluate the implications of this transition for China's labor market,this study employs robust analytical frameworks—specifically input-output analysis combined with structural eecomposition analysis—to quantify China's green employment scale across the 2012—2020 period.Our methodology systematically measures the employment absorption capacity inherent within the domestic green sector while conducting a granular examination of the differential impacts exerted by three critical variables:shifts in labor productivity,structural transformations within the industrial landscape,and oscillations in final demand volume upon green employment creation.Empirical findings yield several significant insights.Firstly,valueadded output from China's green industries demonstrated sustained and robust expansion throughout the examined timeframe.Concurrently,the trajectory of green employment exhibited a distinct V-shaped pattern,characterized by an initial contraction succeeded by a pronounced rebound.Crucially,green employment consistently represented between 4%and 5% of China's total workforce annually during this era.This proportion aligns closely with established estimates documented in comparable international research,reinforcing the validity of our measurements.A critical revelation pertains to the net employment effect.Analysis demonstrates that the employment creation impetus generated by emerging green industries decisively surpassed any displacement effects associated with the transition.This compellingly indicates that China's green sector currently operates within a distinct employment absorption phase.Rather than merely substituting conventional roles,the expansion of green industries is actively contributing to a net augmentation of the nation's overall employment base,effectively driving measurable workforce growth.Further dissection of the influencing factors reveals substantial heterogeneity.The impacts of labor productivity evolution,industrial restructuring,and final demand fluctuations manifested markedly different consequences for employment levels across diverse green industry sub-sectors.Notably,the services segment within the green economy emerged as a vital stabilizing force for the broader labor market throughout the transition,underscoring its essential role in mitigating employment volatility.Expanding the analytical scope,our research identifies a distinctive shift in labor demand patterns within China's green industries.Workforce requirements increasingly bifurcate towards both highly skilled professionals and lower-skilled laborers,simultaneously diminishing relative demand for mid-skilled positions.This dual tendency manifests as a pronounced “skill bias” and fosters an observable trend towards “labor market polarization” within the green economy.The phenomenon suggests a restructuring of occupational demands favoring cognitive/technical expertise at the higher end and manual/service-oriented tasks at the lower end.This study provides practical recommendations for green industry development by analyzing employment trends,offering valuable references for policymakers in formulating industrial transition strategies and addressing labor market challenges during green transformation.These suggestions provide references for relevant government departments in formulating industrial transformation strategies and offer empirical support for resolving conflicts and tensions in the labor market during the green transformation process.
Research on the Competitiveness Evaluation of Digital Industry Cluster Oriented to New Quality Productive Forces
JI Yujun;LIANG Shuang;ZHENG Minjie;In the digital economy era,the rapid emergence of original and disruptive technological innovations has profoundly reshaped the meaning of productivity.Unlike the traditional productivity paradigm reliant on material accumulation and capital deepening,contemporary productivity is increasingly defined by breakthroughs in digital technology,the efficient allocation of data factors,and the restructuring of innovation networks.These shifts reflect the core features of “new quality productive forces”,which emphasize qualitative leaps in production efficiency,industrial upgrading,and systematic innovation.In this context,digital industry clusters have become a crucial engine for high-quality regional development and an important platform for cultivating new quality productive forces.To characterize this dynamic process,an evaluation framework for the competitiveness of digital industry clusters oriented toward new quality productive forces is constructed using the entropy weight method.This framework moves beyond traditional dimensions such as scale,efficiency,and structure,placing greater emphasis on innovation capacity,data factor allocation efficiency,and intra and inter-regional industrial network coordination.Based on this framework,the competitiveness levels of digital industry clusters in 29 typical Chinese cities from2019 to 2022 are systematically evaluated.Further analysis using Dagum Gini coefficient decomposition,and convergence analysis reveals the regional disparities and spatiotemporal evolution of these clusters.The findings indicate that,from the perspective of new quality productive forces,the overall competitiveness of China's digital industry clusters shows a trend of steady improvement.Spatially,a multi-tiered development pattern is observed:cities in eastern China maintain a clear leading advantage,supported by strong industrial foundations,higher innovation intensity,and more developed institutional environments,while central and western cities are gradually catching up through industrial transfer and regional collaboration.Nonetheless,significant heterogeneity persists among cities,with unbalanced development trajectories and no clear convergence trend in the short term,suggesting that regional gaps will not narrow automatically.This underscores the need to foster new quality productive forces according to local conditions,exploring differentiated development paths based on resource endowments,institutional contexts,and development stages.In terms of policy implications,enhancing the competitiveness of digital industry clusters requires phased resource allocation:initial focus on digital infrastructure to lay a solid foundation;medium-term emphasis on inter-regional coordination to facilitate cross-regional flows of data,technology,and talent;and later-stage improvements in governance mechanisms to enhance cluster resilience and sustainability.The upgrading pathway of “factor reorganization,ecological optimization,and governance improvement” offers a practical approach to systematically strengthen cluster competitiveness,providing actionable strategies for regional policymakers and contributing theoretical and policy insights to advance high-quality development in China's digital economy.
Research on the Impact of Artificial Intelligence on Enterprises' New Quality Productive Forces
XU Lin;ZHAO Lele;Artificial intelligence,as the core engine driving a new wave of technological revolution and industrial transformation,holds strategic significance in enabling the development of new quality productive forces.This study empirically examines the impact of artificial intelligence on the development of new quality productive forces and its internal mechanisms based on panel data from Chinese A-share listed companies from 2011 to 2023 at the micro-enterprise level.These findings indicate that artificial intelligence significantly enhances the level of new quality productive forces in enterprises through key pathways such as driving technological innovation,promoting green transformation,and optimizing total factor productivity.This conclusion remains robust after a series of tests,including instrumental variable methods,propensity score matching,and variable replacement.An in-depth analysis from the perspective of institutional logic shows that government logic provides policy support and institutional guarantees,market logic brings competitive pressure and demand incentives,cultural logic fosters an innovation atmosphere and digital literacy,and technological logic builds infrastructure and data ecosystems.These four institutional logics intertwine and resonate synergistically,collectively reinforcing the positive effect of artificial intelligence on new quality productive forces.Heterogeneity analysis further reveals that this empowering effect is particularly pronounced in eastern regions with more complete institutional environments and more efficient factor allocation,regions with higher marketization levels and more robust institutional mechanisms,and state-owned enterprises with superior resource endowments and more timely policy responsiveness.Additionally,the study indicates that artificial intelligence significantly enhances enterprise market valuation and long-term profitability through the mediating mechanism of new quality productive forces,thereby strengthening sustainable development capabilities.This research provides micro-level empirical evidence for understanding how artificial intelligence drives the development of new quality productive forces.It is recommended that the government tailor the construction of AI infrastructure and industrial layout according to local conditions,strengthen the coordinated support of multiple institutional logics including policy,market,and culture,and create a favorable innovation ecosystem;simultaneously,enterprises should proactively seize opportunities brought by AI,deeply integrate AI into innovation systems and green development strategies,accelerate the deep integration of innovation-driven and green transformation,and inject new momentum and build new advantages for promoting high-quality economic development.
Research on Forecasting Development Potential and Competitive Landscape of Key Core Technologies in Low-altitude Economy Industry
YANG Dong;PENG Qianzhao;WEI Zelong;Predicting the development trends of key core technologies and assessing the competitive landscape are of great significance for achieving technological breakthroughs and expanding application scenarios in the low-altitude economy industry.This study begins by constructing a directed and weighted co-occurrence network of International Patent Classification(IPC)codes,taking into account the directionality of knowledge flow and the weighting of co-occurrence relationships.An indicator system is established from three dimensions—position monopoly,knowledge dominance,and technological novelty—to identify key core technologies in the low-altitude economy sector.Subsequently,based on the technology life cycle theory,a Logistic model is employed to fit technology growth curves,predicting the development potential of these key technologies.Finally,an actor cooperation network is constructed to evaluate regional technological competitiveness from two aspects:patent holdings and collaborative contributions,providing a systematic analysis of the competitive posture of various provinces and cities in promising technology fields.Empirical findings reveal that key technologies with development potential include B64U20/87(imaging equipment installation),B64U60/40(foldable landing gear),G06F17/10(complex mathematical operations),H04W24/02(communication optimization),B64U10/14(quadcopter),and G06V20/17(visual optimization).Beijing leads in comprehensive strength across most technological domains,followed by Guangdong,Jiangsu,Zhejiang,and Shaanxi forming a second tier.Based on these conclusions,this study proposes the following policy recommendations:first,enhance technological foresight capacity by establishing a large-scale patent data monitoring platform for regular technology scanning and competition analysis;second,improve the industrial chain ecosystem to promote coordinated development in critical areas such as data processing,flight control systems,and communication navigation;third,establish a regional collaborative innovation mechanism to form a clustered development pattern led by Beijing with multi-regional coordination;fourth,promote differentiated product development by leveraging local advantages to create characteristic application scenarios such as low-altitude logistics and tourism,avoiding homogeneous competition.This study provides a theoretical basis and decision-making reference for governments and enterprises to grasp technological development pathways,identify regional advantages,and formulate development strategies.
Research on the Influence of National Ecological Civilization Construction Demonstration Zone on Urban Resilience
JIANG Feng;LONG Keliang;Urban resilience,as a comprehensive indicator of the resistance,recovery,and adaptability demonstrated by urban systems in response to external shocks,has become a core issue in urban sustainable development.The establishment of the National Ecological Civilization Construction Demonstration Zone aims to enhance ecological civilization construction across cities and achieve sustainable development.At the same time,it plays a positive role in strengthening urban resilience.The entropy weight-deep neural network model(EW-DNN)is constructed to measure urban resilience,and then the National Ecological Civilization Construction Demonstration Zone policy is treated as a quasi-natural experiment.The multiperiod difference in difference method(the Multi-period DID)is adopted to analyze the specific impact of the National Ecological Civilization Construction Demonstration Zone on urban resilience.The results indicate that,firstly,the policy of the National Ecological Civilization Construction Demonstration Zone can significantly enhance urban resilience,the conclusion that has been validated through multiple robustness tests.Secondly,the policy of the National Ecological Civilization Construction Demonstration Zone can enhance urban resilience through channels such as green technology innovation and environmental regulations.Thirdly,the establishment of the National Ecological Civilization Construction Demonstration Zone has a significant improvement effect on the urban resilience of resource-based cities,non-resourcebased cities,eastern cities,cities southeast of the Hu Huanyong Line,and cities with steep slopes,and above.Fourthly,carbon emission intensity plays a negative moderating role between the establishment of the National Ecological Civilization Construction Demonstration Zone and urban resilience.Based on the above research conclusions,relevant departments should persist in promoting the establishment of demonstration zone,scientifically utilizing policy transmission channels,fully leveraging the guiding role of policies in enhancing urban resilience,and promoting the formation of a new pattern of joint construction,joint governance and shared benefits of ecological civilization.
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 demonstrates 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.
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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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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 can solve these problems and thereby promote the development of artificial intelligence technology in enterprises is worthy of in-depth study.Based on this,this paper takes the listed companies in Shanghai and Shenzhen stock markets from 2010 to 2023 as the research sample,and uses 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.
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Multidimensional Opening-up,Technology Diffusion and Consumption Gap between Urban and Rural Residents
ZOU Yang;XU Jingwen;The consumption gap between urban and rural residents is an important indicator for measuring social equity and balanced economic development.During the transition period of opening-up from " exchanging market for technology" to "driving innovation through system",deepening multidimensional opening-up to drive the orderly flow of resources and factors to rural areas is the key path to bridging the consumption gap between urban and rural residents and promoting common prosperity.First,a general equilibrium model that incorporates both urban and rural production sectors and representative household is developed to systematically examine how multidimensional opening-up narrows the urban-rural consumption gap,with particular attention to the role of technology diffusion.Second,a comprehensive evaluation system is constructed,comprising a multidimensional opening-up index(covering trade,investment,tourism,and labor services) and a technology diffusion index(assessing performance,carriers,and support).Using the entropy method,we calculate these indices for 30 Chinese provinces.Finally,based on panel data from 2013 to 2020,this paper empirically analyzes the impact of multidimensional opening-up on the consumption gap and the role of technology diffusion in this process.This paper finds that multidimensional opening-up contributes to narrowing the consumption gap between urban and rural residents.Mechanism test reveals that technology diffusion serves as the key channel through which multidimensional opening-up promotes the narrowing of the consumption gap between urban and rural residents.Heterogeneity analysis shows that among the various dimensions of multidimensional opening-up,trade openness,investment openness,and tourism openness have a significant effect on narrowing the consumption gap between urban and rural residents,while the impact of labor openness on narrowing the consumption gap is not statistically significant.The effect of multidimensional opening-up on narrowing the consumption gap between urban and rural residents is only significant in eastern provinces,provinces with advanced industrial structures,and provinces with high levels of digital inclusive finance.Further analysis shows that multidimensional opening-up has significant spatial spillover effects on technology diffusion and consumption gap between urban and rural residents.According to the analysis above,the following policy suggestions are provided:it is necessary to optimize agricultural services related to multidimensional opening-up and deepen two-way agricultural international cooperation,promote the adoption of international advanced technologies by various entities,strengthen the demonstration and leading role of technology diffusion,and enhance human capital support,coordinate the allocation of open resources,implement regional differentiation strategies,build crossprovince technology collaboration and logistics networks.By clarifying how multidimensional opening-up affects the consumption gap between urban and rural residents and role of technology diffusion,this paper provides theoretical and empirical references for the government to promote the fair distribution of opening dividends and realize common prosperity.
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Research on the Spatiotemporal Evolution and Development Obstacles of New Quality Productive forces's Ecological Environment
XU Hao;FENG Tao;Accelerating the cultivation of new quality productivity is the key to China 's current economic transformation and upgrading,and optimizing the ecological environment for the development of new quality productive forces is the prerequisite for accelerating the cultivation of new quality productive forces.Firstly,based on the connotation of the Marxist concept of productive forces,this paper analyzes the ecological environment factors of the development of new quality productive forces from the perspective of innovation value chain.Then,an evaluation index system for the ecological environment of new quality productive forces is constructed from five dimensions:organizational competition,factor input,development output,market environment and policy incentives.Using data from 30 mainland provinces in China from2013 to 2022 as samples,entropy weight method,spatial Moran index,and obstacle degree model are used for analysis.The results show that the overall ecological environment level of China ' s new quality productive forces is on the rise,with the eastern region significantly better than the central and western regions,and the northeast region deteriorating year by year;In 2022,Guangdong,Jiangsu,and Zhejiang ranked among the top three,while Qinghai had the fastest development with an average annual growth rate of 4.496 %;The eight major economic zones have significant differences,showing a trend of relative convergence and absolute divergence,with the Northwest Economic Zone optimizing the fastest;The south is significantly better than the north,showing a relative and absolute dual trend of development between the north and the south;There is significant spatial agglomeration in the ecological environment of inter provincial new quality productive forces,with spatial agglomeration characteristics transitioning in provinces and cities such as Beijing,Hunan,and Jiangxi.The main obstacles to optimizing the ecological environment of new quality productive forces have shifted from insufficient infrastructure in 2013 to insufficient talent investment in 2022.Talent investment has become the main obstacle to the development of the eastern,central,and western regions,while the administrative environment is the main obstacle to the development of the Northeastern region.There are significant differences in regional and inter provincial obstacles,which need to be overcome according to local conditions.Finally,it is recommended to optimize the ecological environment according to local conditions by optimizing the talent ecology,improving the policy ecology,and enhancing the market ecology,in order to accelerate the formation of new quality productive forces.
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A Review of Technologies on Random Forests
FANG Kuang-nana,b,WU Jian-bina,ZHU Jian-pinga,b,SHIA Bang-changa,b(a.Department of Statistics,School of Economics;b.Data Mining Center,Xiamen University,Xiamen 361005,China)Random Forests is a statistical learning theory,using bootsrap re-sampling method form sample sets,and then combining the tree predictors by majority voting so that each tree is grown using a new bootstrap training set.It is widely applied in medicine,bioinformatics,economics and other fields,because of its high prediction accuracy,good tolerance of noisy data,and the law of large numbers they do not overfit.In this paper we first introduce the concept of random forest and the latest research,then provide some important aspects of applications in economics,and a summary is given in the final section.
[Downloads: 39,911 ] [Citations: 1,960 ] [Reads: 82 ] 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: 60 ] 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: 89 ] 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: 101 ] 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: 82 ] 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: 89 ] 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: 60 ] HTML PDF Cite this article
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