Innovation science and technologiy Volume 1 Issue 12 (2025)
EMPIRICAL ANALYSIS OF TOURISM FLOW FORECASTING IN CENTRAL ASIA BASED REGRESSION MODELS
Suratova, Mokhirakhon
Abstract
Over the past ten years, tourism in Central Asia has grown significantly, especially in Uzbekistan, Kazakhstan,Kyrgyzstan, and Tajikistan. However, due to external shocks and macroeconomic volatility, forecasting tourist arrivalsremains challenging. This study forecasts tourist arrivals for the period 2010–2024 and examines the key determinantsof tourism demand using a multiple regression framework. Annual data were collected from regional and internationalstatistical sources, including indicators such as GDP, inflation, exchange rates, tourist arrivals, and trade openness. Allvariables were transformed into logarithmic form to estimate elasticities, and stationarity was tested using the AugmentedDickey–Fuller (ADF) test. A log-linear regression model was estimated using the Ordinary Least Squares (OLS) methodin R. Model robustness was assessed through diagnostic tests, including Durbin–Watson, Variance Inflation Factor(VIF), Breusch–Pagan, and normality tests. Forecasting accuracy was evaluated using RMSE and MAPE. The resultsindicate that GDP and exchange rates are the most influential determinants of tourism demand, while trade opennessand inflation exhibit statistically significant but relatively smaller effects. The model demonstrates strong short-termforecasting performance. These findings highlight the importance of effective macroeconomic management in sustainingtourism growth in Central Asia and provide a solid methodological and policy-relevant foundation for future econometricresearch in the region.
Tourism forecasting; Central Asia; Regression model; ARIMA; Economic growth; Empirical analysis
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