msueconВестник Московского университета. Серия 6. ЭкономикаLomonosov Economics Journal0130-0105MSUPRESS10.55959/MSU01300105-6-60-6-3msuecon-1492Research ArticleОТРАСЛЕВАЯ И РЕГИОНАЛЬНАЯ ЭКОНОМИКАBRANCH AND REGIONAL ECONOMYАнализ взаимосвязи между оптовыми ценами на электроэнергию и ценами на топливо в РоссииAnalysis of the relationship between wholesale electricity prices and fuel prices in Russiahttps://orcid.org/0000-0001-5295-8876ТомскийС. К.TomskyS. K.

Томский Савва Константинович — старший преподаватель Санкт-Петербургскойшколы экономики и менеджмента

Санкт-Петербург

St. Petersburg

savvatoms@gmail.comhttps://orcid.org/0009-0004-5219-7009МаксимцеваА. В.MaksimtsevaA. V.

Максимцева Анна Викторовна — преподаватель, аспирант Санкт-Петербургскойшколы экономики и менеджмента

Санкт-Петербург

St. Petersburg

amaksimtseva@hse.ruНациональный исследовательский университет «Высшая школа экономики»РоссияHSE UniversityRussian Federation2025040220266065675Copyright © Томский С.К., Максимцева А.В., 20262026Томский С.К., Максимцева А.В.Tomsky S.K., Maksimtseva A.V.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://msuecon.elpub.ru/jour/article/view/1492

Энергетический сектор играет ключевую роль в экономическом развитии каждого государства, особенно такого большого и наделённого богатыми природными ресурсами, как Российская Федерация. В этой статье исследуется влияние цен на топливо на цены на электроэнергию в России. Мы провели детальный анализ существующей научной литературы, чтобы изучить влияние различных факторов на цены энергетических ресурсов на международном уровне. Проведен тест на коинтеграцию и оценена модель векторной авторегрессии (VAR), на основе которой построены функции отклика. В исследовании анализируются помесячные данные с января 2002 по февраль 2024 год по четырём категориям цен на электроэнергию: для населения, непромышленных потребителей, промышленных потребителей и транспорта. Проверка на коинтеграцию с применением теста Энгла – Грейнджера продемонстрировала, что цена на электроэнергию, поставляемую населению существенно связана со всеми видами топлива, в то время как цены на электроэнергию, поставляемую непромышленным потребителям, промышленным потребителям и транспорту интегрируются с газом и углём хотя бы в одном тесте с константой или константой и линейным трендом. Статья вносит значительный вклад в исследование благодаря заполнению пробелов в литературе, поскольку, несмотря на наличие отдельных российских исследований, отсутствуют сопоставимые работы, объединяющие длительный период до 2024 г., четыре направления отпуска электроэнергии и единую VAR-идентификацию ценового канала через топливо — этим обусловлена новизна работы. Было обнаружено, что цены на электроэнергию растут через 1–2 месяца после шоков в стоимости топлива, но это влияние почти полностью исчезает через 1–2 месяца. Это указывает на то, что российская экономика более устойчива к таким потрясениям, но также может свидетельствовать о меньшей конкуренции на электроэнергетическом рынке РФ и требует дальнейшего изучения.

The energy sector plays a pivotal role in the economic development of any country, especially the one as large and resourceful as the Russian Federation. This paper examines the impact of fuel prices on electricity prices in Russia. We conduct an in-depth review of the academic literature to assess how various factors affect energy prices internationally. We then perform a cointegration test and estimate a vector autoregression (VAR), on the basis of which we construct impulse response functions. The analysis uses monthly data from January 2002 to February 2024 for four categories of electricity prices: households, non-industrial users, industrial users, and transportation. Engle–Granger cointegration tests show that the electricity price to households is significantly linked to all fuel types, whereas the prices for non-industrial users, industrial users, and transportation cointegrate with natural gas and coal in at least one specification with a constant or with a constant and a linear trend. The study contributes to the literature by filling a gap: although some Russian studies exist, we are not aware of comparable work that jointly covers a long period up to 2024, four delivery/consumer segments, and a unified VAR identification of the fuel-to-electricity price pass-through — this defines the novelty of the paper. We find that electricity prices tend to rise 1–2 months after fuel-cost shocks, but this effect almost completely dissipates within the following 1–2 months. This suggests that Russian economy is more resilient to such shocks, but it may also point to lower competition in the Russian electricity market and warrants further investigation.

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