Modeling the dynamics and structural shifts in the Russian freight rail industry using hierarchical models under the conditions of trade restrictions[Моделирование Динамики И Структурных Сдвигов В Отрасли Грузовых Железнодорожных Перевозок России С Помощью Иерархических Моделей В Условиях Введения Торговых Ограничений]

the lag in cargo turnover from the pre-crisis level can be analyzed using the property of the structure of the freight transportation database (hierarchical). It will help identify the most affected industries or regions that require support. Objective: to estimate the reduction in cargo turnover for certain types due to the trade restrictions. Methods: hierarchical models. Research results: a new methodological approach to forecasting cargo turnover under sanctions has been developed, which makes it possible to adjust forecasts taking into account the hierarchical structure of data, and empirical assessments of changes in the dynamics of freight traffic for individual groups of goods and directions have been carried out. Main conclusions: the sanctions imposed in 2022 have had an uneven impact on Russian regions. The regions that benefited from the events included the south of the Far East with maximum port load, the agricultural and tourist south, and the Volga region. Among the losers are the Leningrad region and St. Petersburg, subjects traditionally oriented towards Western investments (Kaluga region). Research prospects: the results can be used to formulate mechanisms to get industry back on track by increasing the efficiency of cargo transportation logistics. Forecasts from the upper levels of the hierarchy can be used both to determine the quantitative reduction in imports or exports for individual types of goods, and in general to assess the decline in GDP due to the introduction of trade restrictions.