This study uses time-series techniques and econometric approaches in order to quantify the effects that organising an EU presidency has on the tourism exports of a country. The approach to explain tourism revenues by a time-series intervention model filters out special effects (data discontinuations, exchange rates, events, media reports, etc.) by outlier detection methods, maps influences from trends, the business cycle and seasonal effects in an ARIMA model and depicts the effect of an EU presidency by way of an intervention variable. Using econometric indicator approaches, a country's tourism exports are controlled for seasonal and special influences, habitual effects and demand trends by way of suitable indicators, and a dummy variable is used to test whether the EU presidency made a statistically significant contribution to the revenues from tourism.
EU presidency econometric indicator approach intervention models outlier detection