In this study, we treat the seasonal variation in monthly time series in the context of the Western-European tourism demand for Tunisia, by presenting different techniques of detection of seasonality and the parametric and non-parametric approaches of seasonal adjustment. Then, we compare the...

The widespread availability of internet search data is a new source of high-frequency information that can potentially improve the precision of macroeconomic forecasting, especially in areas with data constraints. This paper investigates whether travel-related online search queries enhance...

Tourism is a growing industry in the Autonomous Region of the Azores. However, little is known about how tourists evaluate this destination, something which certainly constitutes a shortcoming if one takes into consideration that this is a very competitive industry, with new destinations...

This paper estimates the effects of short and long haul volatility (or risk) in monthly Japanese tourist arrivals to Taiwan and New Zealand, respectively. In order to model appropriately the volatilities of international tourist arrivals, we use symmetric and asymmetric conditional volatility...

The effect of imposing different numbers of unit roots on forecasting accuracy is examined using univariate ARMA models. To see whether additional information improves forecasting accuracy and increases the informative forecast horizon, we cross-relate the time series for inbound tourism in...

Sri Lankan tourism market consists all regions of the world. The Asian region is the highest tourist producer to Sri Lankan market. Short term forecasting plays a vital role in the process of operational level decision making in the tourism industry. It is a known fact that the expectations of...

This paper improves short-term forecasting models of monthly tourism arrivals by estimating and evaluating a time-series model with exogenous regressors (ARIMA-X) using a case of Aruba, a small open tourism-dependent economy. Given importance of the US market for Aruba, it investigates...

The purpose of this study is to select the most accurate time series model for forecasting international tourist arrivals to Sri Lanka and generate short-term forecasts that add some benefits for policy makers and decision makers in both the public and private tourism sectors in Sri Lanka....

Extended Characteristic Surface Model (eCSM) is a theoretical tool of general application designed for computing coefficients in stochastic (Monte Carlo) simulations in particular in multi equation stochastic econometric models. Econometric models are most often used for economic analysis of...

This study presents an extension of the Gaussian process regression model for multiple-input multiple-output forecasting. This approach allows modelling the cross-dependencies between a given set of input variables and generating a vectorial prediction. Making use of the existing correlations in...