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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.
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.
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.
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.
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.
ESG Performance Promotes New Quality Productive Forces of Enterprises under the “Double Carbon” Goal
SUN Na;QU Weihua;Under the perspective of the “dual-carbon” goal, the proposal of new quality productive forces is crucial for balancing emission reduction and economic development.Considering that firms are the main players in the development of new quality productive forces, it is important to study whether the ESG performance of firms can enhance their new quality productive forces.The relationship between ESG performance and firms' new quality productive forces is examined using data from Chinese A-share manufacturing firms from 2009 to 2022,and the empirical results show that good ESG performance can significantly enhance firms' new quality productive forces, and the above conclusions are still valid after endogeneity treatment and robustness test.The mechanism analysis shows that good ESG performance affects the new quality productive forces of enterprises through two paths: promoting the disruptive technological innovation of enterprises and improving the efficiency of enterprise labor investment, and green finance can positively regulate the impact of enterprise ESG performance on the new quality productive forces.Heterogeneity analysis shows that for state-owned enterprises, large enterprises and enterprises in the eastern region, the effect of corporate ESG performance on new quality productive forces is more significant.The regression results of carbon emission reduction performance show that ESG performance can significantly reduce the carbon emission intensity of enterprises by empowering them to improve the level of new quality productive forces.The findings not only provide empirical evidence for the emergence of new quality productive forces empowered by enterprises' ESG performance, but also reveal the potential of enterprises' ESG performance in effectively mitigating climate change and reducing the risk of carbon emissions, which can help realize the “dual-carbon” goal.
Research on the Influence Mechanism of Digital Economic Development on Industrial Structure Upgrading
HAN Jian;LI Jiang-yu;The deep integration of digital economy and industrial development is an important driving force for the high-quality development of China's economy in the new era.Based on the panel data of 288 cities in China from 2015 to 2018,three regression models of bidirectional fixed effect, mediating effect and moderating effect are constructed to empirically test and discuss the influence and internal mechanism of digital economy development on the level of urban industrial structure.It is found that the development of digital economy is positively correlated with the upgrading level of industrial structure, and can inhibit the deviation of industrial structure from equilibrium and improve the rationalization level of industrial structure.This conclusion is still valid after a series of robustness tests.At the same time, the digital economy can not only promote the development of industrial structure, but also have a positive impact on the transformation and upgrading of industrial structure through two indirect paths, namely, increasing household consumption and encouraging urban R&D innovation.In addition, the impact of digital economy on the level of industrial structure is also regulated by local government intervention.Under the reasonable administration of local governments, the positive effect of digital economy on industrial transformation and upgrading is more obvious.Finally, the role of digital economic development in promoting the level of industrial structure has regional heterogeneity and urban scale heterogeneity, and the effect of promoting the transformation and upgrading of industrial structure in the central and western regions and megacities is more obvious.The conclusions are helpful to narrow the regional differences of digital economic development and industrial structure level, and provide scientific decision-making basis for the country to further accelerate digital development, standardize local government behavior and formulate accurate industrial policy.
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.