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Forecasting Tourism Demand in Croatia: A Comparison of Different Extrapolative Methods

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  • Tea Baldigara

Abstract

The paper investigates the forecasting accuracy of different basic extrapolative methods in modelling international tourism demand in Croatia. The study compares the results of five basic time-series forecasting methods used to predict foreign tourists¡¯ nights, namely the Na?ve 2 trend, the double moving average with linear trend, the double exponential smoothing, the linear trend time and the autoregressive method. According to the diagnostic all used models show good forecasting performances, but the double moving average method performed the best forecasting performance due to the smallest value of the mean absolute percentage error.

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  • Tea Baldigara, 2013. "Forecasting Tourism Demand in Croatia: A Comparison of Different Extrapolative Methods," Journal of Business Administration Research, Journal of Business Administration Research, Sciedu Press, vol. 2(1), pages 84-92, April.
    • Handle: RePEc:jfr:jbar11:v:2:y:2013:i:1:p:84-92
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    References listed on IDEAS

    as
    1. Chang-Jui Lin & Hsueh-Fang Chen & Tian-Shyug Lee, 2011. "Forecasting Tourism Demand Using Time Series, Artificial Neural Networks and Multivariate Adaptive Regression Splines:Evidence from Taiwan," International Journal of Business Administration, International Journal of Business Administration, Sciedu Press, vol. 2(2), pages 14-24, May.
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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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