Statistical analysis of investment attractiveness of China’s regions

D. Qi, V. Bure
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Abstract

This study is devoted to the application of methods of applied statistics to the study of investment attractiveness of regions of China. Methods of applied statistics are widely used in various engineering research, medicine, economics, sociology, astronomy, ecology, physics, information technology, etc. statistical tools is an integral part of the study. Data taken from the World Bank website and the China Statistical Yearbook. The main topic of this research is: What factors are most strongly associated with investment attractiveness in the economy of modern China? Such a study can only be carried out based on the analysis of economic data, especially in the conditions of the modern digital economy. Consequently, the problem under consideration belongs to the field of applied mathematics. First of all, need to choose a mathematical model and research method. This paper uses the method of regression analysis - one of the most important methods for analyzing economic data. Regression models are mathematical models built from empirical data. Observations (empirical data) are the numerical data on the level of investment in the regions of China, as well as the numerical values of various factors. For each year, a multiple regression model is built using the least squares method, its statistical significance is checked, statistically significant factors are selected (statistically significant coefficients for the factors correspond to them). Calculations are carried out in Excel and SPSS, using subroutines and. Mathematical functions, but at the same time, an algorithm for analyzing the initial data based on a stepwise regression algorithm has been developed, in which only one factor with the least significant coefficient (maximum p-value (t)) is discarded at each step and then an algorithm for choosing the most important factors for investment attractiveness was developed, the essence of this algorithm is that the regression models are compared for each year and how many times each factor was included in the model is calculated algorithms can be attributed to the application of methods informatics in this work. The choice of the most important factors that determine the level of investment attractiveness is made to solve the problem of managing the economy. Attracting investments is important for the effective development of every region, every city, every district. With the receipt of significant investments, it is possible to solve the problems of economic and social development. Determination of the most important factors will make it possible to most effectively solve the problem of managing the economic development of each region, each city, each district.
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中国地区投资吸引力的统计分析
本研究致力于将应用统计学方法应用于中国地区投资吸引力研究。应用统计学的方法被广泛应用于各种工程研究、医学、经济学、社会学、天文学、生态学、物理学、信息技术等领域,是统计学研究中不可缺少的一个组成部分。数据来源于世界银行网站和《中国统计年鉴》。本研究的主要议题是:在现代中国经济中,哪些因素与投资吸引力关系最为密切?这样的研究只能在经济数据分析的基础上进行,尤其是在现代数字经济条件下。因此,所考虑的问题属于应用数学领域。首先,需要选择一个数学模型和研究方法。本文采用回归分析方法,这是分析经济数据最重要的方法之一。回归模型是根据经验数据建立的数学模型。观测值(经验数据)是中国各地区投资水平的数值数据,以及各因素的数值。对每一年采用最小二乘法建立多元回归模型,检验其统计显著性,选取具有统计显著性的因素(各因素对应的系数为统计显著性系数)。计算在Excel和SPSS中进行,使用子程序和。数学函数,但同时,开发了一种基于逐步回归算法的初始数据分析算法,该算法在每一步中只丢弃一个最不显著系数(最大p值(t))的因素,然后开发了选择最重要的投资吸引力因素的算法。该算法的本质是对每年的回归模型进行比较,计算算法中每个因素被纳入模型的次数可归因于方法信息学在本工作中的应用。选择决定投资吸引力水平的最重要因素是为了解决管理经济的问题。吸引投资对每个地区、每个城市、每个地区的有效发展都很重要。有了大量的投资,就有可能解决经济和社会发展的问题。确定最重要的因素将使最有效地解决管理每个地区、每个城市、每个地区的经济发展问题成为可能。
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来源期刊
CiteScore
1.30
自引率
50.00%
发文量
10
期刊介绍: The journal is the prime outlet for the findings of scientists from the Faculty of applied mathematics and control processes of St. Petersburg State University. It publishes original contributions in all areas of applied mathematics, computer science and control. Vestnik St. Petersburg University: Applied Mathematics. Computer Science. Control Processes features articles that cover the major areas of applied mathematics, computer science and control.
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