统计方法在评级编制中的应用特点

V. I. Aleshnikova, T. A. Burtseva, E. A. Divaeva, E. S. Darda, E. M. Bogatyreva
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引用次数: 0

摘要

本文致力于解决评级构建方法的问题,包括动态的可比性和不一致性问题。该研究分析了汇总评级的私人组成部分的程序的方法。人们的注意力集中在国际和国内实践中作为积分表使用的评级的缺点上,其中包括评级的私人组成部分的信息不完整,在开发评级作为积分表的过程中存在不可接受的高水平误差,以及缺乏对其质量的评估。提出了基于等级加权平均和的等级构建方法。私有评级的等级配对系数的平方和与所有私有评级的等级系数的平方和的比率(等级相关的平方矩阵)被用作权重。与现有的方法方法相比,作者提出的方法可以在没有关于私人成分的信息的情况下建立评级。研究结果的新颖之处在于,将私人评级的权重估计方法作为评级的基本组成部分。本文介绍了基于私人评级对俄罗斯中央联邦区各地区进行评级的结果,以实现2021年的国家目标,这证实了拟议方法的充分性。这篇文章可能对统计和区域经济学领域的广泛研究人员感兴趣。
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Features of statistical methods application in rating construction
The article is devoted to solving the problem of rating construction methodology, including issues of comparability in dynamics and inconsistency. The study analyzes approaches to the procedures for aggregating private components of the rating. Attention is focused on the shortcomings of ratings used in international and domestic practice as integral meters, among which are the incompleteness of information on the private components of ratings, an unacceptably high level of error in the development of ratings as integral meters and the lack of evaluation of their quality. The approach to rating construction on the basis of average weighted sum of ranks is offered. The ratio of the sum of the squares of the rank paired coefficients of the private rating to the total sum of the squares of the rank coefficients for all private ratings (the matrix of squares of rank correlations) is used as weights. The approach proposed by the authors, in contrast to the existing methodological approaches, makes it possible to build a rating in the absence of information about private components. The novelty of the study results lies in the method of estimating weights of private ratings as basic components of the rating. The article presents the results of construction a rating of the regions of the Central Federal District in Russia for achieving national goals in 2021 based on private ratings, which confirmed the adequacy of the proposed approach. The article may be of interest to a wide range of researchers in the field of statistics and regional economics.
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42
审稿时长
8 weeks
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