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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">10.34023/2313-6383-2015-0-10-14-25</article-id><article-id custom-type="elpub" pub-id-type="custom">voprstat-271</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>МАТЕМАТИКО-СТАТИСТИЧЕСКИЕ МЕТОДЫ В СОЦИАЛЬНО-ЭКОНОМИЧЕСКИХ ИССЛЕДОВАНИЯХ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>MATHEMATICAL AND STATISTICAL METHODS IN SOCIO-ECONOMIC STUDIES</subject></subj-group></article-categories><title-group><article-title>ПРАКТИКА ИДЕНТИФИКАЦИИ НЕНАБЛЮДАЕМЫХ КОМПОНЕНТ В ТРАЕКТОРИИ ВВП: ПОТЕНЦИАЛЬНЫЙ УРОВЕНЬ И КРАТКОСРОЧНЫЕ РАЗРЫВЫ</article-title><trans-title-group xml:lang="en"><trans-title>IDENTIFICATION OF THE UNOBSERVABLE COMPONENTS IN THE OUTPUT TRAJECTORY: POTENTIAL LEVEL AND GAPS</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>Китрар</surname><given-names>Людмила Анатольевна</given-names></name><name name-style="western" xml:lang="en"><surname>Kitrar</surname><given-names>Ludmila</given-names></name></name-alternatives><email xlink:type="simple">lkitrar@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Липкинд</surname><given-names>Тамара Михайловна</given-names></name><name name-style="western" xml:lang="en"><surname>Lipkind</surname><given-names>Tamara</given-names></name></name-alternatives><email xlink:type="simple">tlipkind@hse.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Остапкович</surname><given-names>Георгий Владимирович</given-names></name><name name-style="western" xml:lang="en"><surname>Ostapkovich</surname><given-names>Georgy</given-names></name></name-alternatives><email xlink:type="simple">gostapkovich@hse.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Чусовлянов</surname><given-names>Дмитрий Сергеевич</given-names></name><name name-style="western" xml:lang="en"><surname>Chusovlyanov</surname><given-names>Dmitry</given-names></name></name-alternatives><email xlink:type="simple">Dchusovlyanov@hse.ru</email><xref ref-type="aff" rid="aff-2"/></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</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>НИУ ВШЭ</institution><country>Россия</country></aff><aff xml:lang="en"><institution>National Research University Higher School of Economics</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2015</year></pub-date><pub-date pub-type="epub"><day>12</day><month>12</month><year>2016</year></pub-date><volume>0</volume><issue>10</issue><fpage>14</fpage><lpage>25</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Китрар Л.А., Липкинд Т.М., Остапкович Г.В., Чусовлянов Д.С., 2016</copyright-statement><copyright-year>2016</copyright-year><copyright-holder xml:lang="ru">Китрар Л.А., Липкинд Т.М., Остапкович Г.В., Чусовлянов Д.С.</copyright-holder><copyright-holder xml:lang="en">Kitrar L., Lipkind T., Ostapkovich G., Chusovlyanov D.</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/271">https://voprstat.elpub.ru/jour/article/view/271</self-uri><abstract><p>В статье систематизированы наиболее известные концепции и определения потенциального выпуска и его разрывов согласно исследованиям различных экономических школ, а также рассмотрена типология основных эконометрических методов оценивания потенциального уровня и разрыва выпуска в динамике ВВП. Авторы дают краткую характеристику механизма действия и возможностей использования различных эконометрических методов, позволяющих проводить статистическую декомпозицию динамики валовой добавленной стоимости с разложением на долгосрочный потенциальный уровень и краткосрочные отклонения - от простой статистической фильтрации до сложных динамических стохастических моделей общего равновесия. В частности, описаны свойства одномерных статистических фильтров, в основе которых лежит статистическое оценивание взаимосвязи только в динамике ВВП, в которой вероятностным отбором декомпозируется долгосрочный уровень без учета каких-либо установок экономической теории. Также анализируются достоинства и недостатки многомерных и структурных методов оценивания потенциального уровня и разрыва ВВП, позволяющих учитывать экономические взаимосвязи посредством включения релевантных дополнительных переменных. В их числе особое внимание уделяется многомерному фильтру Ходрика-Прескотта, а также многомерным моделям с ненаблюдаемыми компонентами, структурным векторным авторегрессионным моделям, производственным функциям, стохастическим динамическим моделям общего равновесия. Проведенный анализ методов декомпозиции и посвященных этой проблеме многочисленных исследований позволяет сделать вывод о том, что процесс декомпозиции ряда на долгосрочную и циклическую компоненты не является тривиальной задачей, имеющей однозначное решение. Многие методы чувствительны к входным данным, в том числе к наличию дополнительных параметров в модели, поэтому более сложные с экономической точки зрения алгоритмы могут показывать худшие результаты, чем алгоритмы на базе статистического анализа, не учитывающие экономическую природу исследуемых рядов. Результаты исследования подтвердили предположение о том, что поиск оптимального метода декомпозиции в различных странах возможен только опытным путем в ходе эмпирических исследований.</p></abstract><trans-abstract xml:lang="en"><p>He authors systematize the most well-known concepts and definitions of potential output and gaps according to the various economic schools approaches. The article also provides a typology of basic econometric methods for estimating potential level and output gap in the national gross product dynamics. The authors give a brief description of various econometric methods of statistical decomposition of the Gross Value Added dynamics for long -term potential level and short-term deviation - from simple statistical filtering to complex dynamic stochastic general equilibrium models. In particular, they describe properties of one -dimensional filters, which are based on statistical evaluation of interrelations only in the output dynamics, with decomposing long-term level by probabilistic methods without taking into account any settings of economic theory. Also, authors examine advantages and disadvantages of multi-dimensional and structural methods for estimating potential levels and output gaps, which allow considering the economic interrelations through inclusion of additional relevant variables. These include multidimensional Hodrick-Prescott filter, multivariate models with unobserved components, structural vector autoregression models, and stochastic dynamic general equilibrium model. The analysis of decomposition methods and numerous studies devoted to this problem lead to conclusion that decomposition of time series for long-term and cyclical components is not a trivial task, which may have a unique solution. Many of decomposition methods are sensitive to input data, including presence of additional parameters in the model, therefore more complex algorithms may show poorer results than algorithms based on statistical analysis, without taking into account an economic nature of investigated series. The results of the research substantiated the assumption that finding the best decomposition method in various countries is possible only through empirical studies.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>конъюнктурный мониторинг</kwd><kwd>бизнес-циклы</kwd><kwd>потенциальный выпуск</kwd><kwd>разрыв ВВП</kwd><kwd>business tendencies monitoring</kwd><kwd>business cycles</kwd><kwd>potential output</kwd><kwd>output gap</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">Brunner K., Meltzer A.H. 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