<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<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">10.34023/2313-6383-2024-31-6-5-19</article-id><article-id custom-type="elpub" pub-id-type="custom">voprstat-1813</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>ОРГАНИЗАЦИЯ И РАЗВИТИЕ ГОСУДАРСТВЕННОЙ СТАТИСТИКИ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>ORGANIZATION AND DEVELOPMENT OF STATE STATISTICS</subject></subj-group></article-categories><title-group><article-title>К вопросу об источниках первичных данных для официальной статистики в России</article-title><trans-title-group xml:lang="en"><trans-title>On the Sources of Primary Data for Official Statistics in Russia</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-0294-2881</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Суринов</surname><given-names>А. Е.</given-names></name><name name-style="western" xml:lang="en"><surname>Surinov</surname><given-names>A. Ye.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Суринов Александр Евгеньевич – д-р экон. наук, профессор, директор по статистическим исследованиям, руководитель департамента статистики и анализа данных, директор Центра экономических измерений и статистики, НИУ «ВШЭ».</p><p>101000, Москва, ул. Мясницкая, д. 20</p></bio><bio xml:lang="en"><p>Alexandr Ye. Surinov – Dr. Sci. (Econ.), Professor; Director for Statistical Studies, Department Head, Department of Statistics and Data Analysis, Director, Economic Statistics Centre of Excellence, National Research University Higher School of Economics (HSE University).</p><p>20, Myasnitskaya Str., Moscow, 101000</p></bio><email xlink:type="simple">surinov@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>2024</year></pub-date><pub-date pub-type="epub"><day>19</day><month>12</month><year>2024</year></pub-date><volume>31</volume><issue>6</issue><fpage>5</fpage><lpage>19</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Суринов А.Е., 2024</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="ru">Суринов А.Е.</copyright-holder><copyright-holder xml:lang="en">Surinov A.Y.</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/1813">https://voprstat.elpub.ru/jour/article/view/1813</self-uri><abstract><p>В статье рассматриваются вопросы трансформации источников первичных данных, необходимых для производства официальной статистики. Эта тема находится в поле зрения Статистической комиссии ООН, ее комитетов и рабочих групп. Мировое статистическое сообщество и национальные статистические системы столкнулись с новым вызовом – революцией данных. Это явление связано с постоянно расширяющейся цифровизацией всех сторон жизни современного человека, появлением новых источников информации, не являющихся результатом традиционных статистических наблюдений. В ряде стран административная статистика начала заменять сбор первичных данных, что привело к фактическому отказу от опросов респондентов и составления отчетности.</p><p>В последние десятилетия феномен больших данных заявил о себе как источник оперативной и детализированной информации о многих явлениях в обществе, экономике и окружающей природной среде. Национальные статистические системы стоят перед выбором, каким образом наиболее эффективно организовать сбор данных в современном мире. Результаты этой дискуссии имеют ключевое значение для международного статистического сообщества, поскольку они влияют на разработку стратегии развития, включая обеспечение условий для интеграции информационных ресурсов и создание инструментов управления данными, полученными из разнообразных источников. Автор рассматривает смену источников данных с учетом необходимости сокращения статистической нагрузки на общество через снижение расходов бюджета и затрат времени респондентов на подготовку и предоставление сведений.</p></abstract><trans-abstract xml:lang="en"><p>The article covers the issues of primary data sources’ transformation for the production of official statistics. This topic is in sight of the UN Statistical Commission and its committees and working groups. The global statistical community and national statistical systems have faced a new challenge – the data revolution. This phenomenon is associated with the ever-expanding digitalization of all aspects of modern life and the emergence of new sources of information that are not the result of classical statistical observations. In some countries, administrative statistics have replaced the collection of primary data. They have practically abandoned surveys and reporting.</p><p>In recent decades, the phenomenon of Big Data has declared itself as a source of operational and detailed information on many phenomena in society, economy and environment. National statistical systems are faced with a choice of how to organize data collection in the modern world most effectively. For the international statistical community, the results of this discussion are of decisive importance in working out a development strategy, including ensuring conditions for the integration of information resources and the creation of tools for managing data obtained from various sources. The author considers the change of data sources, given the need to reduce the statistical burden on society by reducing budget expenditures and the time respondents spend preparing and providing information.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>официальная статистика</kwd><kwd>источники статистических данных</kwd><kwd>статистическое наблюдение</kwd><kwd>административная статистика</kwd><kwd>большие данные</kwd><kwd>опросы населения</kwd></kwd-group><kwd-group xml:lang="en"><kwd>official statistics</kwd><kwd>sources of statistical data</kwd><kwd>statistical observation</kwd><kwd>administrative statistics</kwd><kwd>Big Data</kwd><kwd>population surveys</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Статья подготовлена по материалам исследования, осуществленного в рамках Программы фундаментальных исследований НИУ ВШЭ в 2024 году.</funding-statement><funding-statement xml:lang="en">This article is an output of the research project implemented as part of the Basic Research Program at the National Research University Higher School of Economics (HSE University) in 2024.</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">Supplementing the United Nations Fundamental Principles of Official Statistics: Mapping and Guidance for the United Nations Fundamental Principles of Official Statistics Against Non-Conventional and Non-Traditional Data Sources. Statistical Commission, Fifty-First Session, 3–6 March 2020. URL: https://unstats.un.org/unsd/stat-com/51st-session/documents/BG-Item3q-Supplementing_non-traditional-E.pdf (дата обращения 06.08.2024).</mixed-citation><mixed-citation xml:lang="en">United Nations Statistical Commission. Supplementing the United Nations Fundamental Principles of Official Statistics: Mapping and Guidance for the United Nations Fundamental Principles of Official Statistics Against Non-Conventional and Non-Traditional Data Sources. Statistical Commission, Fifty-First Session, 3–6 March 2020. Available from: https://unstats.un.org/unsd/statcom/51st-session/documents/BG-Item3q-Supplementing_non-traditional-E.pdf (accessed 06.08.2024).</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Report of the Committee of Experts on Big Data and Data Science for Official Statistics. Statistical Commission, Fifty-Forth Session, 28 Febrary – 3 March 2023. E/CN.3/2023/17. URL: https://unstats.un.org/UNSDWebsite/statcom/session_54/documents/2023-17-BigData-R.pdf (дата обращения 08.08.2024).</mixed-citation><mixed-citation xml:lang="en">United Nations Economic and Social Council. Report of the Committee of Experts on Big Data and Data Science for Official Statistics. Statistical Commission, Fifty-Fourth Session, 28 February – 3 March 2023. Document E/CN.3/2023/17. Available from: https://unstats.un.org/UNSDWebsite/statcom/session_54/documents/2023-17-BigData-R.pdf (accessed 08.08.2024).</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Суринов А.Е. Большие данные в официальной статистике: взгляд на проблему // Вопросы статистики. 2023. Т. 30. № 2. С. 5–22. doi: https://doi.org/10.34023/2313-6383-2023-30-2-5-22.</mixed-citation><mixed-citation xml:lang="en">Surinov A.Ye. Big Data in Official Statistics: A View of the Problem. Voprosy Statistiki. 2023;30(2):5–22. (In Russ.) Available from: https://doi.org/10.34023/2313-6383-2023-30-2-5-22.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">United Nations. Guidelines on the Use of Registers and Administrative Data for Population and Housing Census. New York, Geneva: UNECE, 2018. URL: https://unece.org/DAM/stats/publications/2018/ECECESSTAT20184.pdf.</mixed-citation><mixed-citation xml:lang="en">United Nations. Guidelines on the Use of Registers and Administrative Data for Population and Housing Censuses. New York, Geneva: UNECE; 2018. Available from: https://unece.org/DAM/stats/publications/2018/ECECESSTAT20184.pdf.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Alkire S., Foster J. Counting and Multidimensional Poverty Measurement // Journal of Public Economics. 2011. Vol. 95. Iss. 7–8. P. 476–487. doi: https://doi.org/10.1016/j.jpubeco.2010.11.006.</mixed-citation><mixed-citation xml:lang="en">Alkire S., Foster J. Counting and Multidimensional Poverty Measurement. Journal of Public Economics. 2011;95(7-8):476–487. Available from: https://doi.org/10.1016/j.jpubeco.2010.11.006.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Global Multidimensional Poverty Index 2021: Unmasking Disparities by Ethnicity, Caste and Gender. UNDP, OPHI, 2021. URL: https://ophi.org.uk/Publications/GMPI12-2021.</mixed-citation><mixed-citation xml:lang="en">Global Multidimensional Poverty Index 2021: Unmasking Disparities by Ethnicity, Caste and Gender. UNDP, OPHI; 2021. Available from: https://ophi.org.uk/Publications/GMPI12-2021.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">UN Office on Drugs and Crime. World Drug Report 2024. URL: https://www.unodc.org/unodc/en/data-and-analysis/world-drug-report-2024.html.</mixed-citation><mixed-citation xml:lang="en">UNODC. World Drug Report 2024. Available from: https://www.unodc.org/unodc/en/data-and-analysis/world-drug-report-2024.html.</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Управление Организации Объединенных Наций по наркотикам и преступности. Руководство по обследованиям виктимизации. Женева: ООН, 2010. ECE/ CES/4. URL: https://www.unodc.org/documents/data-and-analysis/statistics/crime/Manual_on_Victimization_surveys_Russian.pdf.</mixed-citation><mixed-citation xml:lang="en">UNODC, UNECE. Manual on Victimization Surveys. Geneva: United Nations; 2010. Available from: https://www.unodc.org/documents/data-and-analysis/statistics/crime/Manual_on_Victimization_surveys_Russian.pdf.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">World Bank Group. Poverty and Shared Prosperity 2020. Reversals of Fortune. Washington, DC: World Bank, 2020. URL: https://openknowledge.worldbank.org/server/api/core/bitstreams/611fc6f2-140b-551e-9371-468eec64c552/content.</mixed-citation><mixed-citation xml:lang="en">World Bank Group. Poverty and Shared Prosperity 2020. Reversals of Fortune. Washington, DC: World Bank; 2020. Available from: https://openknowledge.worldbank.org/server/api/core/bitstreams/611fc6f2-140b-551e-9371-468eec64c552/content.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">UNISEF. Child Poverty in Europe and Central Asia Region: Definitions, Measurement, Trends and Recommendations. Geneva: UNICEF, 2017. URL: https://www.unicef.org/eca/media/3396/file/Child-poverty-regional-report.pdf.</mixed-citation><mixed-citation xml:lang="en">UNISEF. Child Poverty in Europe and Central Asia Region: Definitions, Measurement, Trends and Recommendations. Geneva: UNICEF; 2017. Available from: https://www.unicef.org/eca/media/3396/file/Child-poverty-regional-report.pdf.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Международный союз электросвязи. Руководство по измерению доступа к ИКТ и их использования домохозяйствами и отдельными лицами. Издание 2020 года. Женева: Международный союз электросвязи, 2020. URL: https://www.itu.int/en/ITU-D/Statistics/Documents/publications/manual/ITUManualHouseholds2020_R.pdf.</mixed-citation><mixed-citation xml:lang="en">ITU. Manual for Measuring ICT Access and Use by Households and Individuals. 2020 Edition. Switzerland, Geneva: ITU; 2020. Available from: https://www.itu.int/en/ITU-D/Statistics/Documents/publications/manual/ITUManualHouseholds2020_R.pdf.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Eurostat. Guidelines on Small Area Estimation for City Statistics and Other Functional Geographics. 2019 Edition. Luxembourg: Publ. Office of the European Union, 2019. URL: https://ec.europa.eu/eurostat/documents/3859598/10167610/KS-GQ-19-011-EN-N.pdf/3b56be5d-8266-0ee7-7579-7c3e8e63289d?t=1571744473000.</mixed-citation><mixed-citation xml:lang="en">Eurostat. Guidelines on Small Area Estimation for City Statistics and Other Functional Geographics. 2019 Edition. Luxembourg: Publ. Office of the European Union, 2019. Available from: https://ec.europa.eu/eurostat/documents/3859598/10167610/KS-GQ-19-011-EN-N.pdf/3b56be5d-8266-0ee7-7579-7c3e8e63289d?t=1571744473000.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">OECD. Redefining «Urban». A New Way to Measure Metropolitan Areas. Paris: OECD Publ., 2012. URL: https://www.oecd-ilibrary.org/docserver/9789264174108-en.pdf?-expires=1729768781&amp;id=id&amp;accname=guest&amp;check-sum=99DEFC4E08B4FEAF9B3B8441D6EA3863.</mixed-citation><mixed-citation xml:lang="en">OECD. Redefining «Urban». A New Way to Measure Metropolitan Areas. Paris: OECD Publ.; 2012. Available from: https://www.oecd-ilibrary.org/doc-server/9789264174108-en.pdf?expires=1729768781&amp;id=id&amp;accname=guest&amp;checksum=99DEFC4E08B-4FEAF9B3B8441D6EA3863.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">МОТ/MВФ/OЭСР/Евростат/ЕЭК ООН/Всемирный банк. Руководство по индексу потребительских цен: теория и практика. Вашингтон: Международный Валютный Фонд, 2007. URL: https://rosstat.gov.ru/storage/mediabank/cpi_ru(3).pdf.</mixed-citation><mixed-citation xml:lang="en">ILO, IMF, OECD, Eurostat, UN, The World Bank. Consumer Price Index Manual: Theory and Practice. Washington, DC: International Monetary Fund, 2007. (In Russ.) Available from: https://rosstat.gov.ru/storage/mediabank/cpi_ru(3).pdf.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
