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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>The Federal State Budgetary Institution "Scientific Research Institute for Socio-Economic Statistics of the Federal State Statistics Service" (Statistics Research Institute of Rosstat)</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.34023/2313-6383-2025-32-6-43-56</article-id><article-id custom-type="elpub" pub-id-type="custom">voprstat-2015</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>СТАТИСТИКА В СОЦИАЛЬНО-ЭКОНОМИЧЕСКИХ ИССЛЕДОВАНИЯХ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>STATISTICS IN SOCIO-ECONOMIC STUDIES</subject></subj-group></article-categories><title-group><article-title>Торгово-экономические связи России и Китая:  анализ на основе индикаторного подхода</article-title><trans-title-group xml:lang="en"><trans-title>Russia-China Trade and Economic Ties: An Indicator-Based Analysis</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-0974-8723</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Лола</surname><given-names>И. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Lola</surname><given-names>I. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Лола Инна Сергеевна – канд. экон. наук, директор Центра конъюнктурных исследований, Институт статистических исследований и экономики знаний</p><p>101000, г. Москва, Славянская пл., д. 4, стр. 2</p></bio><bio xml:lang="en"><p>Inna S. Lola – Cand. of Sci. (Econ.), Director, Centre for Business Tendency Studies, Institute for Statistical Studies and Economics of Knowledge</p><p>4, Slavyanskaya Sq., Bldg. 2, Moscow, 101000</p></bio><email xlink:type="simple">ilola@hse.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/0009-0000-9314-8984</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Асосков</surname><given-names>Д. Г.</given-names></name><name name-style="western" xml:lang="en"><surname>Asoskov</surname><given-names>D. G.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Асосков Дмитрий Геннадьевич – аналитик Центра конъюнктурных исследований, Институт статистических исследований и экономики знаний</p><p>101000, г. Москва, Славянская пл., д. 4, стр. 2</p></bio><bio xml:lang="en"><p>Dmitry G. Asoskov – Analyst, Centre for Business Tendency Studies, Institute for Statistical Studies and Economics of Knowledge</p><p>4, Slavyanskaya Sq., Bldg. 2, Moscow, 101000</p></bio><email xlink:type="simple">dasoskov@hse.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Национальный исследовательский университет «Высшая школа экономики»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>National Research University Higher School of Economics (HSE University)</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>29</day><month>12</month><year>2025</year></pub-date><volume>32</volume><issue>6</issue><fpage>43</fpage><lpage>56</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Лола И.С., Асосков Д.Г., 2025</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru">Лола И.С., Асосков Д.Г.</copyright-holder><copyright-holder xml:lang="en">Lola I.S., Asoskov D.G.</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/2015">https://voprstat.elpub.ru/jour/article/view/2015</self-uri><abstract><p>В статье представлена оценка внешнеторговых связей Российской Федерации и Китайской Народной Республики с применением системы статистических индикаторов международной торговли. Целью исследования является количественный анализ структуры и динамики товарооборота между Россией и Китаем на основе расчета индексов интенсивности торговли, взаимозависимости торговли, сравнительных экспортных преимуществ, сравнительных импортных недостатков и комплементарности торговли.</p><p>Источником данных послужила платформа Международного торгового центра (ITC) TradeMap.</p><p>Результаты анализа показывают устойчиво высокий уровень торговой активности двух стран. В 2024 г. объем их взаимного товарооборота достиг рекордной отметки в 244,8 млрд долларов США, при этом индексы интенсивности как импорта России из Китая, так и экспорта в обратном направлении также обновили свои максимальные значения, составив 3,72 и 3,07 соответственно. В то же время установлена значительная асимметрия в российско-китайской торговле: значение индекса взаимозависимости торговли для России (14,53) почти в пять раз превышает значение данного показателя для Китая (3,07).</p><p>Характеризуя товарную структуру взаимной торговли двух стран, сравнительные преимущества и недостатки, авторы выделили в качестве наиболее конкурентоспособной товарной группы российского экспорта в 2024 г. «Удобрения», в то время как Китай испытывал высокую потребность в импорте продукции товарной группы «Руда, шлак и зола».</p><p>Комплексный индекс комплементарности торговли достиг в 2024 г. максимального с 2017 г. значения – 1,38, что подтверждает высокую степень взаимодополняемости экономик анализируемых стран, особенно в сегменте сырьевой продукции. Китай в торговле с Россией в основном специализируется на экспорте продукции высокотехнологичного производства и нуждается в импорте товаров первичной переработки; Россия же обладает сравнительными преимуществами в реализации товаров, относящихся главным образом к сырьевым группам, а высокотехнологичную продукцию экспортирует в значительно меньшей степени. Для дальнейшего развития партнерских внешнеторговых отношений с Китаем и, в частности, диверсификации структуры экспорта России необходимы целенаправленная государственная поддержка, а также изменения в институциональной системе.</p></abstract><trans-abstract xml:lang="en"><p>This paper presents an assessment of the foreign trade relations between the Russian Federation and the People's Republic of China using a system of statistical indicators for international trade. The goal of this study is to conduct a quantitative analysis of the structure and dynamics of bilateral trade, based on the calculation of the Trade Intensity Index, the HM Index of trade interdependence, the Export Revealed Comparative Advantage Index, the Import Revealed Comparative Disadvantage Index, and the Trade Complementarity Index. The data source was the ITC TradeMap platform.</p><p>The results show consistently high levels of trade activity between the two countries: in 2024, the volume of trade reached a record high of 244.8 billion US dollars, while the Trade Intensity Index of both imports from China to Russia and exports in the opposite direction also updated their own maximum values, amounting to 3.72 and 3.07, respectively. The study revealed a significant asymmetry in the bilateral trade of the two countries: the value of the HM Trade Interdependence Index for Russia (14.53) was almost five times higher than that for China (3.07).</p><p>Characterizing the commodity structure of mutual trade between the two countries, comparative advantages and disadvantages, the authors identified «Fertilizers» as the most competitive commodity group of Russian exports in 2024, while China had a high demand for imports of products from the «Ore, Slag and Ash» commodity group.</p><p>The comprehensive Trade Complementarity Index has reached a peak in 2024 of 1.38, the highest value since 2017. This indicates a high degree of complementarity between the economies of the countries, particularly in the raw materials sector. In trade with Russia, China mainly specializes in the export of high-tech products and needs to import primary processed goods. Russia, in contrast, has comparative advantages in the sale of goods belonging mainly to raw material groups, and exports high-tech products to a much lesser extent. To further develop foreign trade partnership with China and diversify Russia's export structure, targeted government support is needed, as well as changes in the institutional system.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>Россия</kwd><kwd>Китай</kwd><kwd>торговые индексы</kwd><kwd>сравнительные преимущества</kwd><kwd>торговая политика</kwd></kwd-group><kwd-group xml:lang="en"><kwd>Russia</kwd><kwd>China</kwd><kwd>trade indices</kwd><kwd>comparative advantages</kwd><kwd>trade policy</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Статья подготовлена в рамках Программы фундаментальных исследований Национального исследовательского университета «Высшая школа экономики».</funding-statement><funding-statement xml:lang="en">The article is based on the study funded by the Basic Research Program of the HSE University.</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">Turgel I., Vlasova N., Xu L. 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