imiМеждународная аналитикаJournal of International Analytics2587-84762541-9633MGIMO University10.46272/2587-8476-2023-14-1-22-36imi-466Research ArticleИССЛЕДОВАТЕЛЬСКИЕ СТАТЬИRESEARCH ARTICLESКак исследовать политику санкций? Стратегия эмпирического исследованияHow to Study the Policy of Sanctions? The Vision of Empirical ResearchТимофеевИ. Н.TimofeevI. N.

Иван Николаевич Тимофеев, к. полит. н., генеральный директор, доцент

кафедра политической теории

119454

Проспект Вернадского 76

Москва

Ivan N. Timofeev, CEO, PhD in Political Science, Associate Professor

Department of Political Theory

119454

Prospect Vernadskogo 76

Moscow

itimofeev@russiancouncil.ruРоссийский совет по международным делам; МГИМО МИД РоссииРоссияRussian International Affairs Council; Moscow State Institute of International Relations (MGIMO-university)Russian Federation2023130420231412236Copyright © Тимофеев И.Н., 20232023Тимофеев И.Н.Timofeev I.N.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.interanalytics.org/jour/article/view/466

   В мировой исследовательской практике накоплен значительный опыт исследования политики санкций. В России внимание к данной тематике существенно возросло на фоне масштабного применения санкций в отношении отечественной экономики. В практическом плане возросла потребность в объективных эмпирических исследованиях, базирующихся как на сборе и анализе баз данных по тематике односторонних ограничительных мер, так и на изучении отдельных случаев (кейсов). Потребность в таких исследованиях ставит целый ряд эпистемологических вопросов. Как именно выстроить эмпирический анализ политики санкций? Каким может быть оптимальный алгоритм выстраивания сбора и анализа информации в данной области? О чем говорит уже существующий опыт отдельных элементов подобных исследований? В статье рассматривается стратегия эмпирического исследования санкций. Ключевой тезис состоит в том, что оптимальной стратегией является движение от баз данных множества событий в области санкций к изучению отдельных кейсов. Наряду с количественной информацией, база данных позволяет выявлять типичные и аномальные случаи, подтверждая или опровергая отдельные рабочие гипотезы. Тезис раскрывается на примерах авторских баз данных – базы данных санкционных событий, базы штрафов Министерства финансов США в отношении бизнеса, базы данных законопроектов по санкциям Конгресса США.

   Scholars worldwide have amassed a wealth of knowledge on the use of economic sanctions, relying on either the analysis of large datasets or the examination of particular cases. The extensive sanctions levied against Russia have spurred research into their implementation and impact among Russian scholars, necessitating impartial empirical research. This demand raises a number of epistemological questions, such as what the strategy for understanding sanctions empirically should be, how to handle data and its processing, and what implications the existing literature, both domestically and abroad, has for approaching empirical research on sanctions. The crux of the matter is the generation of quantitative datasets of multiple sanctions events and cases, which serves as an essential starting point for empirical research. This approach helps to differentiate between “normal” and “deviant” cases, thereby justifying further sampling of cases for in-depth qualitative analysis. The article vividly illustrates this point by relying on the author’s databases on sanctions events, U. S. government enforcement actions, and U.S. Congress legislation processes on sanctions.

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The authors declare that there are no conflicts of interest present.