WIFO Research Seminar with Ulrich Gunter (Modul University Vienna)
Ulrich Gunter from Modul University Vienna spoke at the WIFO Research Seminar on 15 September 2020 about the predictive
ability of "Facebook likes" in tourism demand forecasting. WIFO economist Oliver Fritz contributed a commentary.
Commentary: Oliver Fritz (WIFO) Please send – up to one day before the event – an informal registration to email@example.com,
if you are interested in attending this lecture. For online participation: GoToMeeting link will be submitted after registration
Organised by: Austrian Institute of Economic Research
Using data for the period 2010M06-2017M02, this study investigates the possibility of predicting total tourist arrivals to
four Austrian cities (Graz, Innsbruck, Salzburg, and Vienna) from LIKES of posts on the Facebook pages of the destination
management organisations of these cities. Google Trends data are also incorporated in investigating whether forecast models
with LIKES and/or with Google Trends deliver more accurate forecasts. To capture the dynamics in the data, the autoregressive
distributed lag (ADL) model class is employed. Taking into account the daily frequency of the original LIKES data, the mixed
data sampling (MIDAS) model class is employed as well. While time-series benchmarks from the naive, error-trend-seasonal,
and autoregressive moving average model classes perform best for Graz and Innsbruck across forecast horizons and forecast
accuracy measures, ADL models incorporating only LIKES or both LIKES and Google Trends generally outperform their competitors
for Salzburg. For Vienna, the MIDAS model including both LIKES and Google Trends produces the smallest forecast accuracy measure
values for most forecast horizons.