俄罗斯联邦北极地区主体的地区社会经济异质性指标比较分析及其综合评估

Upasak Bose, Kuzmenko Yulia Gennadevna, Greiz Georgy Markovich
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引用次数: 0

摘要

俄罗斯联邦北极区(AZRF)是一个独特的地理区域,各种社会经济因素对其稳定和发展起着重要作用。为了准确评估和评价 AZRF 的整体社会经济进步,应综合考虑各种因素,从而全面了解该地区的社会经济稳定和发展。然而,关于俄罗斯北极地区社会经济发展的现有文献缺乏对各种指标的综合分析。在本文中,作者选择了最能描述特定地区(此处指 AZRF)社会经济状况的五个异构指标,并对 2014-2019 年期间进行了综合分析。这些指标涉及社会经济方面,如地区生产总值和该地区获得的投资额,这反过来又导致就业机会和居民收入水平的变化,以及他们可获得的社会福利。分析所使用的数学工具是模糊逻辑理论,其框架是确定模糊集的子直方图。这种方法具有可扩展性,可以扩展到任何数量的不同性质的指标,因为最终得分将在 [0, 1] 的范围内,从而使区域比较和排名成为可能。使用这种方法,可以在单个指标层面和整体层面对研究对象进行排序,从而确定每个研究对象和整个 AZRF 的优缺点。在整体层面上,根据所获得的综合得分,各主体被排序为克拉斯诺雅尔边疆区、阿尔汉格尔斯克州、科米共和国、摩尔曼斯克州、亚马尔-涅涅茨自治区、卡累利阿共和国、萨哈共和国(雅库特)、涅涅茨自治区和楚科奇自治区。JEL 代码R11
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative Analysis of Regional Socioeconomic Heterogeneous Indicators in the Subjects of the Arctic Zone of the Russian Federation and Their Integral Assessment
The Arctic Zone of Russian Federation (AZRF) is a unique geography with diverse socioeconomic factors playing significant roles in its stability and progress. In order to accurately assess and evaluate the overall socioeconomic progress of AZRF, the heterogeneous factors should be considered in an integrated manner, which will give a holistic view of the socioeconomic stability and development of the region. The available literature on socioeconomic development of Russian Arctic region however suffers from lack of integrated analysis of heterogeneous indicators. In this article, the authors have selected five heterogeneous indicators which best describe the socioeconomic condition of a given region, which in this case is AZRF and performed integral analysis for the time period 2014–2019. The indicators refer to socioeconomic aspects such as gross regional product and amount of investments received by the region, which in turn leads to changes in employment opportunities and income level of the population along with social benefits available to them. The mathematical instrument used for the analysis is the theory of fuzzy logic in the framework of determination of the subdirect image of a fuzzy set. This method is scalable and can be extended to any number of indicators of diverse nature since the final score will be in the range of [0, 1] making comparison of regions and ranking possible. Using this method, the subjects were ranked at individual indicator level and at holistic level as a result of which the advantages and disadvantages of each subject and the AZRF as a whole were determined. At holistic level, the subjects were ranked as Krasnayarsky Krai, Arkhangelsk Oblast, Republic of Komi, Murmansk Oblast, Yamalo-Nenets Autonomous Okrug, Karelia Republic, Sakha Republic (Yakutia), Nenets Autonomous Okrug and Chukotka Autonomous Okrug based on the integral scores obtained. JEL Code: R11
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