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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">10.34023/2313-6383-2021-28-2-128-139</article-id><article-id custom-type="elpub" pub-id-type="custom">voprstat-1276</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>ИЗ РЕДАКЦИОННОЙ ПОЧТЫ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>FROM THE EDITORIAL MAIL</subject></subj-group></article-categories><title-group><article-title>Пространственный анализ взаимосвязи изменения доходов и потребления населения на основе панельных данных</article-title><trans-title-group xml:lang="en"><trans-title>Spatial Analysis of the Relationship Between Income and Consumption of the Population Based on Panel Data</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-9876-9202</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Лакман</surname><given-names>И. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Lakman</surname><given-names>I. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Лакман Ирина Александровна – канд. техн. наук, доцент, зав.  лабораторией исследования социально-экономических  проблем регионов</p><p>450076, г. Уфа, ул. З. Валиди, 32</p></bio><bio xml:lang="en"><p>Irina A. Lakman – Cand. Sci. (Tech.), Assistant Professor, Head,  Laboratory of Research in Socio-Economic Problems of Regions</p><p>32, Zaki Validi St., Ufa, 450076</p></bio><email xlink:type="simple">Lackmania@mail.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/0000-0002-1004-0722</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Тимирьянова</surname><given-names>В. М.</given-names></name><name name-style="western" xml:lang="en"><surname>Timiryanova</surname><given-names>V. M.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Тимирьянова Венера Маратовна – канд. экон. наук, доцент,  старший научный сотрудник, зам. зав. лаборатории  исследования социально-экономических проблем регионов</p><p>450076, г. Уфа, ул. З. Валиди, 32</p></bio><bio xml:lang="en"><p>Venera M. Timiryanova – Cand. Sci. (Econ.), Assistant Professor,  Senior Researcher, Deputy Head, Laboratory of Research in Socio-Economic Problems of Regions</p><p>32, Zaki Validi St., Ufa, 450076</p></bio><email xlink:type="simple">79174073127@mail.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/0000-0002-7698-8858</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Попов</surname><given-names>Д. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Popov</surname><given-names>D. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Попов Денис Владимирович – канд. техн. наук, доцент, и. о.  заведующего кафедрой «Цифровые технологии и моделирование»</p><p>450064, г. Уфа., ул. Космонавтов, 1</p></bio><bio xml:lang="en"><p>Denis V. Popov – Cand. Sci. (Tech.), Acting Head, Department of  Digital Technologies and Modelling</p><p>1, Kosmonavtov St., Ufa, 450064</p></bio><email xlink:type="simple">popov.denis@inbox.ru</email><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Башкирский государственный университет</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Bashkir State University</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>Уфимский государственный нефтяной технический университет</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Ufa State Petroleum Technological University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2021</year></pub-date><pub-date pub-type="epub"><day>03</day><month>05</month><year>2021</year></pub-date><volume>28</volume><issue>2</issue><fpage>128</fpage><lpage>139</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Лакман И.А., Тимирьянова В.М., Попов Д.В., 2021</copyright-statement><copyright-year>2021</copyright-year><copyright-holder xml:lang="ru">Лакман И.А., Тимирьянова В.М., Попов Д.В.</copyright-holder><copyright-holder xml:lang="en">Lakman I.A., Timiryanova V.M., Popov D.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://voprstat.elpub.ru/jour/article/view/1276">https://voprstat.elpub.ru/jour/article/view/1276</self-uri><abstract><p>В статье отражены результаты исследования влияния динамики, региональных особенностей и видовой структуры доходов населения на его потребление. Возможность исследовать пространственные зависимости и территориальные эффекты, проявляющиеся в течение определенного времени, появилась благодаря авторегрессионным пространственным моделям, построенным на панельных данных. В статье описаны особенности таких моделей, последовательность проведения расчетов, а также представлены модифицированные тесты, позволяющие обосновать выбор спецификации модели.Расчеты проводились по данным 83 субъектов Российской Федерации (кросс-секционных наблюдений) в период 2010–2019 гг. (10 временных периодов). Проведенный анализ показал, что и доходы населения, и оборот розничной торговли, во многом определяющий уровень и структуру потребления населения, пространственно зависимы. Построенная модель пространственной ошибки с фиксированными эффектами показала положительную связь между фиксируемыми объемами потребления в соседних территориях. В рамках модели также были подтверждены и ранее выявляемые взаимосвязи: положительное влияние среднедушевых доходов и негативное влияние индекса Джини на объемы потребления. Построенная модель с фиксированными эффектами позволила выделить индивидуальные эффекты территорий, визуализированные на картограмме. На основе полученных оценок определены несколько групп территорий с общими свойствам и особенностями.В отличие от ранее выстраиваемых моделей разработанная авторами авторегрессионная модель пространственной ошибки, построенная на панельных данных, позволила одновременно учесть территориальную неоднородность и пространственную зависимость среднедушевых доходов и оборота розничной торговли, расширив существующие представления о связи потребления и доходов населения. Это в свою очередь создает условия для выработки управленческих решений, которые учитывают не выявляемые ранее особенности и повышают их обоснованность.</p></abstract><trans-abstract xml:lang="en"><p>The article presents results of a study on influence of population dynamics, regional characteristics and the type structure of income on consumption. The ability to investigate spatial dependencies and territorial effects over time was made possible by autoregression spatial models built on panel data. The article describes features of such models, sequence of calculations, and also presents modified tests to justify the choice of the model specification.Calculations were made using data from 83 constituent entities of the Russian Federation (cross-sectional observations) for 2010–2019 (10 time periods). The analysis showed that both population income and retail turnover, which largely determine the level and structure of population consumption, have spatial dependencies. The built spatial error model with fixed effects showed a positive influence on population consumption in the neighboring territories. The model also confirmed previously identified relationships: the positive impact of average per capita income and the negative impact of the Gini index on consumption. The built model with fixed effects allowed to isolate the individual effects of the territories, visualized using cartogram. On the basis of these assessments, several groups of territories with common properties and characteristics have been identified.Unlike previously built models, the authors’ spatial error autoregression model, built on panel data, took into account both the geographical heterogeneity and spatial dependence of average per capita income and retail turnover, expanding the existing understanding of the relationship between consumption and income. This, in turn, enables management decisions that take into account previously undetected features and enhance their validity.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>показатели доходов населения</kwd><kwd>показатели потребления населения</kwd><kwd>панельные данные</kwd><kwd>корреляционно-регрессионный метод</kwd><kwd>пространственная модель на панельных данных</kwd><kwd>пространственная автокорреляция данных</kwd></kwd-group><kwd-group xml:lang="en"><kwd>population income indicators</kwd><kwd>population consumption indicators</kwd><kwd>panel data</kwd><kwd>correlation and regression method</kwd><kwd>spatial panel data model</kwd><kwd>spatial autocorrelation of data</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Исследование выполнено в рамках государственного задания Министерства науки и высшего образования Российской Федерации (код научной темы FZWU-2020-0027).</funding-statement><funding-statement xml:lang="en">The study was carried out within the framework of the state assignment of the Ministry of Science and Higher Education of the Russian Federation (code of scientific theme: FZWU-2020-0027).</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">Аганбегян А.Г. 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