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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">voprstat</journal-id><journal-title-group><journal-title xml:lang="ru">Вопросы статистики</journal-title><trans-title-group xml:lang="en"><trans-title>Voprosy Statistiki</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2313-6383</issn><issn pub-type="epub">2658-5499</issn><publisher><publisher-name></publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.34023/2313-6383-2023-30-2-43-52</article-id><article-id custom-type="elpub" pub-id-type="custom">voprstat-1552</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>СТАТИСТИЧЕСКИЕ МЕТОДЫ В СОЦИАЛЬНО-ЭКОНОМИЧЕСКИХ ИССЛЕДОВАНИЯХ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>STATISTICAL METHODS IN SOCIO-ECONOMIC STUDIES</subject></subj-group></article-categories><title-group><article-title>Межрегиональная дифференциация и неоднородность последствий пандемийных ограничений в России</article-title><trans-title-group xml:lang="en"><trans-title>Interregional Differentiation and Heterogeneity of the Consequences of Pandemic Restrictions in Russia</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-0624-7269</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Бозо</surname><given-names>Н. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Bozo</surname><given-names>N. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Наталья Владимировна Бозо, канд. экон. наук, доцент, доцент кафедры</p><p>кафедра экономической теории и прикладной экономики</p><p>630073</p><p>пр-т Карла Маркса, д. 20</p><p>Новосибирск</p></bio><bio xml:lang="en"><p>Natalia V. Bozo, Cand. Sci. (Econ.), Associate Professor, Associate Professor of the Department</p><p>Department of Economic Theory and Applied Economics</p><p>630073</p><p>20, Karl Marx Ave.</p><p>Novosibirsk</p></bio><email xlink:type="simple">bozo_nstu@ngs.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-5705-0880</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Шипкова</surname><given-names>О. Т.</given-names></name><name name-style="western" xml:lang="en"><surname>Shipkova</surname><given-names>O. T.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Ольга Тарасовна Шипкова, канд. экон. наук, доцент, доцент кафедры</p><p>Институт экономики и управления промышленными предприятиями имени В. А. Роменца</p><p>кафедра экономики</p><p>119049</p><p>Ленинский пр-т, д. 4, стр. 1</p><p>Москва</p></bio><bio xml:lang="en"><p>Olga T. Shipkova, Cand. Sci. (Econ.), Associate Professor, Associate Professor of the Department</p><p>College of Economics &amp; Industrial Management named after V. A. Romenets</p><p>Department of Economics</p><p>119049</p><p>4, Leninsky Prospekt, Bld. 1</p><p>Moscow</p></bio><email xlink:type="simple">olship@inbox.ru</email><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Новосибирский государственный технический университет</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Novosibirsk State Technical University</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>Национальный исследовательский технологический университет «МИСИС»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>National University of Science and Technology MISIS</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2023</year></pub-date><pub-date pub-type="epub"><day>16</day><month>04</month><year>2023</year></pub-date><volume>30</volume><issue>2</issue><fpage>43</fpage><lpage>52</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Бозо Н.В., Шипкова О.Т., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Бозо Н.В., Шипкова О.Т.</copyright-holder><copyright-holder xml:lang="en">Bozo N.V., Shipkova O.T.</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://voprstat.elpub.ru/jour/article/view/1552">https://voprstat.elpub.ru/jour/article/view/1552</self-uri><abstract><p>   Цель исследования – анализ особенностей экономического развития регионов России под влиянием различных социально-экономических факторов и дифференциация групп регионов в зависимости от реализации в них мер государственного регулирования экономической деятельности в пандемийный период.</p><p>   Анализ проводился с использованием статистических методов (прежде всего, методов статистических группировок и корреляционно-регрессионного анализа). На основе изучения научных публикаций отечественных и зарубежных исследователей по рассматриваемой проблематике изложены концептуально-методологические принципы оценки изменения экономической активности в российских регионах после введения ограничительных мер разного уровня жесткости. Для выявления влияния исследуемых факторов построена регрессионная модель, включающая такие статистические показатели, как индекс промышленного производства, уровень безработицы, доля городского населения, доля валовой добавленной стоимости (ВДС) региона в ВДС страны, число предприятий малого и среднего бизнеса (без микропредприятий) на 10 тыс. человек населения, доля региона в производстве продукции всех российских добывающих предприятий, коэффициент открытости региона, среднедушевые денежные доходы населения, уровень бедности. В заключительной части статьи представлены результаты исследования, свидетельствующие о том, что пандемийные ограничения в зависимости от степени их жесткости оказывали различное воздействие на экономику регионов. Авторы подчеркивают разнородность изменений факторов детерминации экономической активности регионов под влиянием ограничительных мер со стороны органов управления, в частности, региональных властей.</p></abstract><trans-abstract xml:lang="en"><p>   The purpose of the study is to analyze the features of the economic development of Russian regions under the influence of various socio-economic factors and the differentiation of region groups depending on the implementation of state regulation of economic activity measures in them during the pandemic period.</p><p>   The analysis was carried out using statistical methods (primarily methods of statistical groupings and correlation-regression analysis). The conceptual and methodological principles for assessing changes in economic activity in Russian regions after the introduction of restrictive measures of different levels of severity are outlined based on the study of Russian and foreign scientific publications on the issues under consideration. A regression model uses to identify the influence of the studied factors. To identify the impact of the studied factors, the authors built a regression model that included the following statistical indicators: index of industrial production, unemployment rate, share of the urban population, share of the region's gross value added (GVA), number of small and medium-sized enterprises (excluding micro-enterprises) per 10,000 population, share of the region in the production of all Russian mining enterprises, region openness coefficient, average per capita monetary income of the population, poverty level. The final part of the article presents the results of the study indicating that pandemic restrictions, depending on the degree of their severity, had a different impact on the economy of the regions. The authors emphasize the heterogeneity of changes in the factors determining the economic activity of regions under the influence of restrictive measures on the part of governments, particularly regional authorities.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>экономическое развитие</kwd><kwd>региональная экономика</kwd><kwd>ковидные ограничения</kwd><kwd>статистические методы</kwd><kwd>региональная статистика</kwd><kwd>межрегиональная дифференциация</kwd><kwd>эмпирический анализ</kwd></kwd-group><kwd-group xml:lang="en"><kwd>economic development</kwd><kwd>regional economy</kwd><kwd>COVID restrictions</kwd><kwd>statistical methods</kwd><kwd>regional statistics</kwd><kwd>interregional diversity</kwd><kwd>empirical analysis</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">Rasoulinezhad E. Regionalism Approach Under the COVID-19 Circumstances / E. 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