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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">umovest</journal-id><journal-title-group><journal-title xml:lang="ru">Статистика и Экономика</journal-title><trans-title-group xml:lang="en"><trans-title>Statistics and Economics</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2500-3925</issn><publisher><publisher-name>Plekhanov Russian University of Economics</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.21686/2500-3925-2022-6-40-52</article-id><article-id custom-type="elpub" pub-id-type="custom">umovest-1669</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ЭКОНОМИЧЕСКОЕ РАЗВИТИЕ РЕГИОНОВ И РЕГИОНАЛЬНАЯ СТАТИСТИКА</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>THE ECONOMIC DEVELOPMENT OF THE REGIONS AND REGIONAL STATISTICS</subject></subj-group></article-categories><title-group><article-title>Использование отраслевой структуры экономики для отбора регионов-конкурентов (на примере Амурской области)</article-title><trans-title-group xml:lang="en"><trans-title>Using the Sectoral Structure of the Economy to Select Competing Regions (on the Example of the Amur Region)</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Васильева</surname><given-names>А. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Vasilieva</surname><given-names>A. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Анжелика Валерьевна Васильева</p><p>Благовещенск</p></bio><bio xml:lang="en"><p>Angelica V. Vasilieva</p><p>Blagoveshchensk</p></bio><email xlink:type="simple">vavangel@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Амурский государственный университет</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Amur State University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2022</year></pub-date><pub-date pub-type="epub"><day>28</day><month>12</month><year>2022</year></pub-date><volume>19</volume><issue>6</issue><fpage>40</fpage><lpage>52</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Васильева А.В., 2022</copyright-statement><copyright-year>2022</copyright-year><copyright-holder xml:lang="ru">Васильева А.В.</copyright-holder><copyright-holder xml:lang="en">Vasilieva A.V.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://statecon.rea.ru/jour/article/view/1669">https://statecon.rea.ru/jour/article/view/1669</self-uri><abstract><p>Одним из этапов статистического исследования конкурентоспособности региона является отбор регионов-конкурентов. Цель исследования. Целью статьи является формирование статистической совокупности регионов-конкурентов на основе отраслевой структуры экономики.Материалы и методы. В качестве методов исследования в данной статье выбраны метод основного массива, факторный, кластерный методы, статистические методы. Для проведения исследования использованы статистические данные Росстата. Для выполнения расчетов рассматривалась ВДС в структуре ОКВЭД2 за 2019 г.Результаты. С помощью факторного анализа выполнена группировка 19 видов экономической деятельности регионов по сходству и различиям. В результате образовалось 6 факторов, каждый из которых собрал зависимые виды экономической деятельности. Использование кластерного анализа позволило сформировать группы регионов, имеющих похожую отраслевую структуру экономики. В исследовании приняло участие 85 регионов Российской Федерации. Кластерный анализ позволил решить методологическую проблему определения границ интервалов ВДС по отдельным видам экономической деятельности при отборе регионов-конкурентов. В работе показано, что для Амурской области в качестве регионов-конкурентов следует рассматривать 9 субъектов Российской Федерации. Регионы данного кластера объединяет высокая доля валовой добавленной стоимости по видам деятельности «Транспортировка и хранение», «Государственное управление», «Торговля». При этом конкурентами являются регионы из разных федеральных округов: 70% регионов Дальневосточного федерального округа, 20% – Южного ФО, 10% – Сибирского ФО. Основными результатами исследования являются следующие: 1) выявлена высокая вариация субъектов Российской Федерации в 2019 г. по виду экономической деятельности «Добыча полезных ископаемых» и «Обрабатывающие производства»; 2) выполнена группировка 19 видов экономической деятельности регионов методом факторного анализа; 3) проведен кластерный анализ регионов Российской Федерации по отраслевой структуре валовой добавленной стоимости за 2019 г.; получено 5 кластеров. Заключение. В настоящей работе показано, что отбор регионов-конкурентов необходимо выполнять, используя отраслевую структуру экономики региона. Учет специализации региона является важным требованием методики отбора. Преимуществом авторской методики является ее универсальность, объективность и отражение специализации региона. В качестве направления дальнейших исследований следует рассмотреть определение специализации регионов с помощью коэффициентов локализации и на ее основе формирование статистической совокупности регионов-конкурентов. Представленная выборка регионов необходима для проведения оценки их конкурентоспособности.</p></abstract><trans-abstract xml:lang="en"><p>One of the stages of the statistical study of the competitiveness of a region is the selection of competing regions.Purpose of the study. The purpose of the article is to form a statistical set of regions-competitors based on the sectoral structure of the economy.Materials and methods. As research methods in this article, the method of the main array, factorial, cluster methods, statistical methods are chosen. The statistical data of Rosstat were used for the study. To perform the calculations, the GVA was considered in the structure of Russian National Classifier of Types of Economic Activity2 for 2019. Results. With the help of factor analysis, 19 types of economic activity of the regions were grouped according to similarities and differences. As a result, six factors were formed, each of which collected dependent types of economic activity. The use of cluster analysis made it possible to form groups of regions with a similar sectoral structure of the economy. The study involved 85 regions of the Russian Federation. Cluster analysis made it possible to solve the methodological problem of determining the boundaries of GVA intervals for certain types of economic activity in the selection of competing regions.The paper shows that for the Amur Region, nine regions of the Russian Federation should be considered as competing regions. The regions of this cluster are united by a high share of gross value added by the types of activity “Transportation and storage”, “Public administration”, “Trade”. At the same time, competitors are regions from different federal districts: 70% of the regions of the Far Eastern Federal District, 20% of the Southern Federal District, 10% of the Siberian Federal District. The main results of the study are the following: 1) a high variation of the regions of the Russian Federation in 2019 was revealed by the type of economic activity “Mining” and “Manufacturing”; 2) a grouping of 19 types of economic activity of the regions was carried out using the factor analysis method; 3) a cluster analysis of the regions of the Russian Federation was carried out according to the sectoral structure of gross value added for 2019; five clusters were received. Conclusion. This paper shows that the selection of competing regions must be carried out using the sectoral structure of the region’s economy. Consideration of the region’ specialization is an important requirement of the selection methodology. The advantage of the author’s methodology is its universality, objectivity and reflection of the specialization of the region. As a direction for further research, one should consider determining the specialization of regions using localization coefficients and, on its basis, the formation of a statistical set of competing regions. The presented sample of regions is necessary for assessing their competitiveness.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>регионы Российской Федерации</kwd><kwd>методика отбора регионов-конкурентов</kwd><kwd>факторный анализ</kwd><kwd>кластерный анализ</kwd><kwd>отраслевая структура экономики</kwd><kwd>статистические методы</kwd><kwd>конкурентоспособность региона</kwd><kwd>ОКВЭД2</kwd><kwd>метод к-средних</kwd></kwd-group><kwd-group xml:lang="en"><kwd>regions of the Russian Federation</kwd><kwd>methodology for selecting competing regions</kwd><kwd>factor analysis</kwd><kwd>cluster analysis</kwd><kwd>sectoral structure of the economy</kwd><kwd>statistical methods</kwd><kwd>regional competitiveness</kwd><kwd>Russian National Classifier of Types of Economic Activity2</kwd><kwd>k-means method</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Крутиков В.К., Якунина М.В., Левкина В.Н. 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