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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">ecpolicy</journal-id><journal-title-group><journal-title xml:lang="ru">Экономическая политика</journal-title><trans-title-group xml:lang="en"><trans-title>Economic Policy</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1994-5124</issn><issn pub-type="epub">2411-2658</issn><publisher><publisher-name>Economic Policy</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.18288/1994-5124-2020-1-40-63</article-id><article-id custom-type="elpub" pub-id-type="custom">ecpolicy-742</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>Макроэкономический анализ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>Macroeconomic analysis</subject></subj-group></article-categories><title-group><article-title>Оценка траектории темпов трендового роста ВВП России в ARX-модели с ценами на нефть</article-title><trans-title-group xml:lang="en"><trans-title>Estimating Time-Varying Long-Run Growth Rate of Russian GDP in the ARX Model with Oil Prices</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>Полбин</surname><given-names>А. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Polbin</surname><given-names>A. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Андрей Владимирович Полбин —  кандидат экономических наук, заведующий лабораторией математического моделирования экономических процессов; заведующий лабораторией макроэкономического моделирования,</p><p>117517, Москва, пр. Вернадского, 82;</p><p>125009, Москва, Газетный пер., 3–5. </p></bio><bio xml:lang="en"><p>Andrey V. Polbin, Cand. Sci. (Econ.),</p><p>82, Vernadskogo pr., Moscow, 117517;</p><p>3–5, Gazetny per., Moscow, 125009.</p></bio><email xlink:type="simple">apolbin@iep.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>РАНХиГС; Институт экономической политики  им. Е. Т. Гайдара</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Russian Presidential Academy of National Economy and Public Administration; Gaidar Institute for Economic Policy</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2020</year></pub-date><pub-date pub-type="epub"><day>28</day><month>02</month><year>2020</year></pub-date><volume>15</volume><issue>1</issue><fpage>40</fpage><lpage>63</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Полбин А.В., 2020</copyright-statement><copyright-year>2020</copyright-year><copyright-holder xml:lang="ru">Полбин А.В.</copyright-holder><copyright-holder xml:lang="en">Polbin 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://www.ecpolicy.ru/jour/article/view/742">https://www.ecpolicy.ru/jour/article/view/742</self-uri><abstract><p>В работе оценивается траектория темпов трендового роста ВВП России на основе модели авторегрессии с экзогенными переменными и меняющимся во времени параметром темпа трендового роста, который предположительно описывается процессом случайного блуждания. При высокой зависимости российской экономики от экспорта сырьевых товаров условия торговли были выбраны как контрольная экзогенная переменная для динамики ВВП. В качестве прокси-переменной для условий торговли рассматривались реальные цены на нефть и временной ряд отношения дефлятора экспорта к дефлятору импорта. Для эконометрического оценивания модель ARX была представлена в виде модели ненаблюдаемых компонент и оценена с помощью метода максимального правдоподобия с использованием фильтра Калмана. В результате эконометрического анализа был сделан выбор в пользу модели с ценами на нефть в качестве прокси-переменной для условий торговли в связи с ее более высокой прогнозной силой в эксперименте псевдовневыборочного (pseudo-out-ofsample) прогнозирования. Показано, что в первой половине 2000-х годов темпы трендового роста составили примерно 4% в год, что можно интерпретировать как восстановительный рост после трансформационного спада. Более высокие фактически достигнутые темпы роста за этот период объясняются интенсивным ростом мировых цен на нефть. Далее потенциал восстановительного роста был исчерпан, и после кризиса 2008 года темпы трендового роста продолжительное время находились на уровне 2% в год. Однако после кризиса 2014 года темпы трендового роста начали неуклонно снижаться и к началу 2019-го составили примерно 1% в год, что можно интерпретировать как воздействие санкций и международной напряженности на экономическое развитие России. Результаты эконометрического анализа модели на данных по потреблению домохозяйств и по инвестициям также говорят о темпах трендового роста примерно 1% в год в настоящее время.</p></abstract><trans-abstract xml:lang="en"><p>The paper estimates the path of trend growth rates for Russian GDP based on an autoregressive model with exogenous variables and with a time-varying parameter of trend growth, which, by assumption, is described by a random walk process. In conditions of a high dependence of the Russian economy on commodity exports, terms of trade are used as a control exogenous variable for GDP dynamics. For the purpose of econometric estimation, the ARX model is presented as an unobserved components model and estimated using the maximum likelihood method with the Kalman filter applied. It is shown that in the first half of the 2000s the trend growth rate was at 4%, which can be interpreted as recovery growth after a transformational recession. The higher growth rates actually achieved during this period are explained by the intensive growth of world oil prices. Later, the potential for recovery growth was exhausted, and after the crisis of 2008 the rates of trend growth were remaining at the level of 2% per year for a long period of time. However, following the 2014 crisis, trend growth rates began to decline steadily, and had reached about 1% per year by the beginning of 2019, which can be interpreted as the impact of sanctions and geopolitical uncertainty on the economic development of the Russian Federation. The results of an econometric analysis of the model on household consumption and investment data also suggest that the trend growth rate is approximately 1% per year at present.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>модели с меняющимися во времени параметрами</kwd><kwd>долгосрочные темпы роста ВВП</kwd><kwd>экономический рост</kwd><kwd>российская экономика</kwd><kwd>цены на нефть</kwd><kwd>условия торговли</kwd><kwd>потребление</kwd><kwd>инвестиции</kwd></kwd-group><kwd-group xml:lang="en"><kwd>time-varying parameters model</kwd><kwd>long-run growth of GDP</kwd><kwd>Russian economy</kwd><kwd>oil prices</kwd><kwd>terms of trade</kwd><kwd>investment</kwd><kwd>consumption</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Исследование выполнено при финансовой поддержке РФФИ в рамках научного проекта № 18-31000365.</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">Айвазян С. 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