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FORECASTING TOURIST FLOWS IN THE REGIONS OF THE VOLGA FEDERAL DISTRICT FOR 2026–2028: SCENARIO‑BASED APPROACH AND KEY DRIVERS OF GROWTH

Published in MOSCOW ECONOMIC JOURNAL · Volume 11, Issue 8, 2026 · Pages 237–254 · Rubric: Economic Geography
DOI: https://doi.org/10.55186/2413046X_2026_11_8_120 · EDN: ZGAEWO
Received: 06.08.2026 Accepted: 16.09.2026 Published: 17.09.2026 Language of publication: ru-RU
The article addresses the forecasting of tourist flows in the regions of the Volga Federal District for the medium term (2026–2028). The relevance is driven by spatial disparities in tourism development and the instability of current trends, necessitating evidence-based management decisions. The aim is to develop short-term forecasts for all 14 constituent entities using a combination of linear extrapolation and scenario-based approaches, and to identify key growth drivers. The study utilizes Rosstat time-series data for 2004–2025. Forecasting is performed under three scenarios: pessimistic (5% growth), baseline (linear trend), and optimistic (9% growth). Additionally, shifts in tourist demand structure in 2024–2025 are analyzed, highlighting the most dynamic tourism segments. The results confirm a sustained positive trend: even under the pessimistic scenario, the total tourist flow is expected to grow by 16% by 2028 compared to 2025. Spatial polarization persists, with the Republic of Tatarstan and Nizhny Novgorod Oblast leading, while the Republic of Mari El, Mordovia, and Penza Oblast show minimal projected values. Cultural-educational, event, gastronomic, automotive, and nature-oriented tourism are identified as key drivers. The study concludes that combining forecasting methods is advisable and that targeted support for depressed regions is essential.
tourist flow forecasting, Volga Federal District, scenario approach, linear extrapolation, spatial polarization, types of tourism
Funding
This work wasfunded by a grant from the Academy of Sciences of the Republic of Tatarstan provided to higher education institutions, scientific and other organizations to support human resource development plans in terms of encouraging their research and academic staff to defend doctoral dissertations and conduct research activities (Agreement No. 12/2025-PD-KFU dated December 22, 2025).
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