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Tourism demand modelling and forecasting – a case study of Croatia

Tourism is the most important economic sector in Croatia and a significant source of profit for a wide range of activities. Croatia is predominantly a service-based economy, with the service sector accounting for about 60% of the total Gross Domestic Product. Among the service industries, tourism, above all, contributes to almost 20% of the Croatia’s Gross Domestic Product. Consequently, it is becoming increasingly difficult to ignore the importance of tourism for Croatia’s future economic development. The enhancement of Croatian tourism competitiveness is based on a set of policy goals postulated by official institutions and bodies, i.e. to profile Croatia as one of the high-quality tourist destinations in the Mediterranean and Europe, to increase earnings by rising the spending in tourism, to extend the tourist season, and to develop a sustainable and competitive tourism. The achievement of such and other tourism development goals necessitates of a synergic action of all counterparts and stakeholders involved in the tourism sector, but above all it necessitates of an accurate and combined qualitative and quantitative analysis, modelling and forecasting. Based on those premises the paper investigates the application of time-series based quantitative methods in Croatian tourism demand modelling and forecasting. In the literature there emerge two categories of quantitative methods, the time-series models and the econometric approaches which analyse the casual relationship between the dependent and the explanatory variables. The paper researches the potentials of time-series models in analysing and researching tourism demand with a particular attention on tourism demand in Croatia, as a significant international tourism destination. Time-series models, and mostly the integrated autoregressive moving-average models (ARIMA), have been widely used in the past for tourism demand modelling and forecasting. Models and accurate forecasts of tourism demand provide crucial information for tourism policymaking in both, government and business sectors. Modelling and forecasting are important elements in tourism demand planning, designing, routing and enhancing. One of the primary challenges facing tourism management and development is to produces systematic, prompt and accurate tourism demand forecasts. Time series analysis should be considered a tool for explaining, researching and forecasting tourist demand in Croatia, as it certainly allows extracting the maximum amount of meaningful and comprehensive information contained in the empirical tourism demand series in order to provide models and accurate forecasts and future development plans.

Croatian tourism; tourism demand; forecasting; time-series models; seasonal ARIMA models; Box-Jenkins approach

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