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Title: Using a global vector autoregression to conditionally forecast tourism exports and tourism export prices Authors:  Ulrich Gunter - MODUL University Vienna (Austria) [presenting]
Abstract: The purpose is to analyze the ex-ante projected trajectories of real tourism exports and relative tourism export prices of the EU-15 conditional on expert real GDP growth forecasts for the global economy that were provided by the OECD for the years 2013 to 2017. To this end, a global vector autoregression (GVAR) is applied to a panel data set ranging from 1994Q1 to 2013Q3 for a cross section of 45 countries. In line with economic theory, growing global tourist income combined with decreasing relative destination price ensures, in general, increasing tourism demand for the politically and macroeconomically distressed EU-15. However, the conditionally forecast increases in tourism demand are under-proportional for some EU-15 member countries. Thus, rather than simply relying on increases in tourist income at the global level, tourism planners and developers in the EU-15 should address the relatively low price-competitiveness of the member countries in order to counter the rising competition for global market shares and to ensure future tourism export earnings.