Abstract
The purpose of this paper is to provide an insight into the modelling and forecasting of unknown events or shocks that can affect international tourist arrivals. Time-dependence is vital for summarising scattered findings. The usefulness of econometric forecasting has been recently confirmed by the pandemic and other events that have affected the world economy and, consequently, the tourism sector. In the study, a single Slovenian dataset is input for the analysis of tourist arrivals. Vector autoregressive modelling is used in the modelling process. The data vector from the premium research is extended up to 2022. The latter is an ex-post empirical study to show the validity of the ex-ante predictions. This paper analyses the synthesis of ex-ante predictions which fill the gap in the ex-ante forecasting literature. The study of previous events is relevant for research, policy and practice, with various implications.
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