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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">mir</journal-id><journal-title-group><journal-title xml:lang="ru">МИР (Модернизация. Инновации. Развитие)</journal-title><trans-title-group xml:lang="en"><trans-title>MIR (Modernization. Innovation. Research)</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2079-4665</issn><issn pub-type="epub">2411-796X</issn><publisher><publisher-name>School of Public Administration</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.18184/2079-4665.2023.14.3.398-415</article-id><article-id custom-type="edn" pub-id-type="custom">bsfrhu</article-id><article-id custom-type="elpub" pub-id-type="custom">mir-1533</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>ИННОВАЦИИ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>INNOVATION</subject></subj-group></article-categories><title-group><article-title>Стресс-тестирование развития регионов России в условиях внешнеэкономических ограничений</article-title><trans-title-group xml:lang="en"><trans-title>Stress testing of the development of Russian regions in the context of external economic restrictions</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-0714-7764</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Данилова</surname><given-names>И. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Danilova</surname><given-names>I. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Данилова Ирина Валентиновна, доктор экономических наук, профессор; профессор, кафедра экономической теории, региональной экономики, государственного и муниципального управления</p><p>Scopus ID: 55970505600</p><p>Челябинск</p></bio><bio xml:lang="en"><p>Irina V. Danilova, Doctor of Economic Sciences, Professor; Professor of the Department of Economic Theory, Regional Economics, State and Municipal Management</p><p>Scopus ID: 55970505600</p><p>Chelyabinsk</p></bio><email xlink:type="simple">danilovaiv@susu.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/0000-0002-6971-746X</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Резепин</surname><given-names>А. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Rezepin</surname><given-names>A. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Резепин Александр Владимирович, кандидат экономических наук, доцент; доцент, кафедра экономической теории, региональной экономики, государственного и муниципального управления</p><p>Scopus ID 57190415900</p><p>Челябинск</p></bio><bio xml:lang="en"><p>Aleksandr V. Rezepin, Candidate of Economic Sciences, Associate Professor; Associate Professor of the Department of Economic Theory, Regional Economics, State and Municipal Management</p><p>Scopus ID 57190415900</p><p>Chelyabinsk</p></bio><email xlink:type="simple">avrezepin@susu.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/0000-0001-8346-6612</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Правдина</surname><given-names>Н. B.</given-names></name><name name-style="western" xml:lang="en"><surname>Pravdina</surname><given-names>N. V.</given-names></name></name-alternatives><bio xml:lang="en"><p>Natalya V.  Pravdina,  Candidate  of  Economic  Sciences;  Associate  Professor  of  the  Department  of  Industrial  Economics  and  Project Management</p><p>Chelyabinsk</p></bio><email xlink:type="simple">pravdinanv@susu.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Южно-Уральский государственный университет (национальный исследовательский университет)</institution><country>Россия</country></aff><aff xml:lang="en"><institution>South Ural State University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2023</year></pub-date><pub-date pub-type="epub"><day>12</day><month>10</month><year>2023</year></pub-date><volume>14</volume><issue>3</issue><fpage>398</fpage><lpage>415</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Данилова И.В., Резепин А.В., Правдина Н.B., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Данилова И.В., Резепин А.В., Правдина Н.B.</copyright-holder><copyright-holder xml:lang="en">Danilova I.V., Rezepin A.V., Pravdina N.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://www.mir-nayka.com/jour/article/view/1533">https://www.mir-nayka.com/jour/article/view/1533</self-uri><abstract><p>Цель исследования – разработать модель стресс-тестирования влияния внешних ограничений на экономику регионов и провести диагностику ударопрочности развития в условиях реализации шоковых событий.</p><sec><title>Методы</title><p>Методы. Исследование базируется на концепции BANI-мира, теориях экономической динамики и шоков, теории пространственной экономики. Методика исследования включает применение сценарного подхода при разработке модели стресс-тестирования регионов, алгоритма идентификации «ожидаемого воздействия» шока на основе метода машинного обучения – искусственной нейронной сети.</p></sec><sec><title>Результаты работы</title><p>Результаты работы. Обобщение научных публикаций по теме исследования, анализ шоковых событий, постшоковых последствий (2006–2022 гг.) позволили обосновать теоретическую и прикладную целесообразность тестирования и дифференциации реакции российских регионов на внешние ограничения, применение критериев «ударопрочности» развития, классификации экономического пространства и идентификации территорий с «ударопрочной» и «неударопрочной» реакцией на шоки. Разработана модель стресс-тестирования регионов, идентифицированы производственно-отраслевые (67,6% важности) и пространственные (32,4%) факторы стабилизации, идентифицированы зоны уязвимости к ограничениям 2022–2023 гг., определены индустриальные регионы с потенциалом «неударопрочного» развития экономики при шоковых нагрузках.</p></sec><sec><title>Выводы</title><p>Выводы. Реакция регионов на внешние шоки и ограничения (длительность периода снижения и интенсивность восстановительного роста) специфична и определяется сочетанием уникальных пространственных и производственных характеристик регионов. Результаты исследования в части теоретических выводов о неоднородности регионов с позиции реакции на внешние ограничения и методического подхода к стресс-тестированию их развития расширяют теорию пространственной экономики, имеют прикладное значение для оценки «ударопрочности» субъектов РФ, прогнозирования экономического развития, формирования стратегии государственного управления регионами.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>Purpose</title><p>Purpose: is to develop the model for stress testing of the impact of external constraints of Russian regions in the context of foreign economic constraints 2022–2023.</p></sec><sec><title>Methods</title><p>Methods: the research is based on the theory of economic dynamics, regional economy and spatial development, the concept of the BANI world; the methodological basis of the study is a scenario approach to the formation of the stress testing model and the algorithm for determining the expected impact based on the machine learning method – the artificial neural network.</p></sec><sec><title>Results</title><p>Results: the study of scientific publications on the research topic, analysis of shock events, post-shock consequences (2006–2022) made it possible to substantiate feasibility of testing and differentiating the response of Russian regions to external constraints, applying the criteria of “shock-resistant” development, classifying economic space and identifying the territory with “shock-resistant” and “non-shockresistant”reactions. The model of regions stress testing has been developed, industrial and sectoral (67.6% importance) and spatial (32.4%) stabilization factors have been identified, areas of vulnerability to the restrictions of 2022-2023 and industrial regions with the potential for “non-shock-resistant” type of reaction have been identified.</p><p>Conclusions and Relevance: the reaction of regions to external economic shocks (the duration of the decline period and the intensity of recovery growth) is determined by the totality of the production and spatial characteristics of the regions. The results of the study are important for the development of the theory of regional economy; they can be used byfederal and regional executive authorities of the Russian Federation.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>стресс-тестирование</kwd><kwd>внешние шоки</kwd><kwd>ударопрочность экономики</kwd><kwd>экономическое развитие</kwd><kwd>дифференциация регионов</kwd><kwd>индустриальные регионы</kwd><kwd>нейронные сети</kwd></kwd-group><kwd-group xml:lang="en"><kwd>stress testing</kwd><kwd>external shocks</kwd><kwd>shock resistance of the economy</kwd><kwd>economic development</kwd><kwd>regional differentiation</kwd><kwd>industrial regions</kwd><kwd>neural networks</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Исследование выполнено за счет гранта Российского научного фонда и Челябинской области № 23-28-10167, https://rscf.ru/project/23-28-10167/.</funding-statement><funding-statement xml:lang="en">The research was funded by Russian Science Foundation and Chelyabinsk Region № 23-28-10167, https://rscf.ru/en/project/23-28-10167/.</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Mariotti S. 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