Home  Journals  Financial Analytics: Science and Experience  2(376) - 2026 April–June

Assessment of tourist demand and forecast of outbound flows from Russia: Econometric analysis

Received: 29 December 2025

Accepted: 28 January 2026

Available online: 28 May 2026

Subject Heading: ASSESSMENT AND APPRAISAL ACTIVITIES

JEL Classification: С01, С13, С52, L83, Z32

Pages: 39-52

https://doi.org/10.24891/esbjzu

Subject. The economic nature of Russian citizens' tourist demand for destinations in the Middle East in the context of a deep geopolitical reorientation that began in 2022.
Objectives. Determination of the income and price elasticity of outbound flows, measurement of the effect of visa liberalization, as well as the development of a reasonable scenario forecast of the volume of departure and income of the countries of the region until 2028.
Methods. The methodology of econometric modeling based on data from Rosstat, the Bank of Russia, national tourism administrations and a representative survey of 3,286 Russian citizens was used.
Results. An empirical assessment revealed a high income elasticity of demand (1.84). The price elasticity was –0.92, indicating a significant but not critical sensitivity to the cost of the tour. Transportation costs also affect demand (elasticity –0.67), confirming the importance of direct flights. The strongest effect is from the abolition of visas: the tourist flow increased by 2.18 times. Forecast for 2028: 1.92 million tourists (baseline scenario), total revenues of the region's countries – 11.1 billion dollars. At the same time, Saudi Arabia and Qatar show maximum revenue growth rates of 3.6 and 3.2 times, respectively, reflecting a shift in demand to the premium segment.
Conclusions. The estimates obtained confirm that the liberalization of visa policy and the stability of real incomes of the population are key drivers of growth. The results of the study provide the basis for developing a government strategy for interaction with the region based on quantitative rather than expert assessments.

Keywords: Middle East, tourist attractiveness, five-block model, visa policy, tourism geopolitics

References:

1. Lickorish B.L., Jenkins C.L. Introduction to Tourism. Oxford; New York, Butterworth-Heinemann, 1997, 244 p.
2. Lim C. Review of international tourism demand models. Annals of Tourism Research, 1997, vol. 24, iss. 4, pp. 835–849. DOI: 10.1016/S0160-7383(97)00049-2
3. Witt S.F., Witt C.A., Hope C. Modeling and Forecasting Demand in Tourism, London, Academic Press, 1992, 195 p.
4. Papatheodorou A. Exploring the evolution of tourism resorts. Annals of Tourism Research, 2004, vol. 31, iss. 1, pp. 219–237. DOI: 10.1016/J.ANNALS.2003.10.004
5. Rozanova T.P. [Anti-crisis measures to reduce the consequences of the impact of sanctions on the tourism industry of Russia]. Upravlencheskie nauki, 2022, vol. 12, no. 2, pp. 45–54. (In Russ.) DOI: 10.26794/2304-022X-2022-12-2-45-54 EDN: DZQPCP
6. Simonyan G.A., Saryan A.A. [Features of the formation of tourist flows in modern conditions]. Sovremennaya nauchnaya mysl', 2021, no. 2, pp. 181–189. (In Russ.) DOI: 10.24412/2308-264X-2021-2-181-189 EDN: UEXRIG
7. Leonidova E.G., Rumyantsev N.M. [Scenario modeling of tourism services consumption in Russia]. Ekonomicheskie i sotsial'nye peremeny: fakty, tendentsii, prognoz, 2023, vol. 16, no. 2, pp. 35–51. (In Russ.) DOI: 10.15838/esc.2023.2.86.2 EDN: XURHSI
8. Khudyakova T.A., Glinskikh I.E. [Influence of variants of currency market for the state of the Russian touristic industry]. Vestnik NGIEI, 2018, no. 5, pp. 76‒86. (In Russ.) EDN: XNDGBF
9. Witt S.F., Witt C.A. Forecasting tourism demand: A review of empirical research. International Journal of Forecasting, 1995, vol. 11, iss. 3, pp. 447–475. DOI: 10.1016/0169-2070(95)00591-7
10. Bo Peng, Haiyan Song, Crouch G.I., Witt S.F. A meta-analysis of international tourism demand elasticities. Journal of Travel Research, 2014, vol. 54, iss. 5, pp. 611–633. DOI: 10.1177/0047287514528283
11. Bednova M.A., Ratnikova T.A. [Econometric analysis of the demand for the incoming tourism in Russia]. Prikladnaya ekonometrika, 2011, no. 1, pp. 97–113. (In Russ.) EDN: NUEJQH
12. Klimova T.B., Vishnevskaya E.V., Anoprieva E.V. [The structure and dynamics of tourist flows: trends and determining factors]. Servis v Rossii i za rubezhom, 2017, vol. 11, no. 5, pp. 6–18. (In Russ.) DOI: 10.22412/1995-042X-11-5-1 EDN: ZBIXMP
13. Lebedeva S.A., Radygina E.G., Oshkordina A.A. [Express-analysis of the tourist flow between Russia and Central Asia: country and regional aspects]. Ekonomika Tsentral'noi Azii, 2023, vol. 7, no. 4, pp. 379–407. (In Russ.) DOI: 10.18334/asia.7.4.120169 EDN: MYYQYV
14. Aslanargun А., Mammadov M., Yazici B., Yolacan S. Comparison of ARIMA, neural networks and hybrid models in time series: tourist arrival forecasting. Journal of Statistical Computation and Simulation, 2007, vol. 77, iss 1, pp. 29–53. DOI: 10.1080/10629360600564874
15. Kozlov D.A. [Forecasting of Russian outbound tourism]. Mezhdunarodnyi zhurnal prikladnykh i fundamental'nykh issledovanii, 2016, no. 1-2, pp. 232–237. (In Russ.) EDN: VJFXTR
16. Kopyrin A.S., Vidishcheva E.V. [Development of a model of the influence of tourist flows on the stability of the tourist territory (region)]. Teoreticheskaya i prikladnaya ekonomika, 2022, no. 2, pp. 46–56. (In Russ.) DOI: 10.25136/2409-8647.2022.2.36623 EDN: TDKDOW
17. Dickey D.A., Fuller W.A. Distribution of the Estimators for Autoregressive Time Series with a Unit Root. Journal of the American Statistical Association, 1979, vol. 74, no. 366, pp. 427–431. DOI: 10.2307/2286348
18. Engle R.F., Granger C.W.J. Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 1987, vol. 55, no. 2, pp. 251–276. DOI: 10.2307/1913236

View all articles of issue

ISSN 2311-8768 (Online)
ISSN 2073-4484 (Print)

Journal current issue

ISSUE 2 JUNE 2026

Archive