Authors: Konstantinos Koronios, Lazaros Ntasis, Alkistis Papaioannou, Panagiotis Dimitropoulos, Dashi Marinela

Title: Tourism: Forecasting the recovery of the COVID-2019’s great patient

Abstract

Coronavirus (COVID-19) outbreak, which began in Wuhan, China, has been spread to people everywhere in the world - for the first time in a century. The easy transmission of COVID-19 has forced governments to impose travel restrictions, lockdowns, and shutdowns to impose social distancing measures in their attempt to obstruct farther rapid spread of the disease and to preserve the efficacy of national healthcare systems.

The tourism sector has experienced one of the first, and probably most severe, shocks caused by the international spread of COVID-19: international tourist arrivals are estimated to drop to 78% causing a loss of $1.2 trillion in export revenues from tourism and $120 million direct tourism Job cuts representing the largest decline in the history (UNWTO, 2020).

During the last decades, the world has faced various diseases with academic research exploring how they affected tourism (Karabulut et al., 2020) supporting that those diseases cause a significant decline in tourist arrivals. Research investigating, measuring and predicting the COVID-19 tourism impacts is important in order to eliminate ‘casualties’, draft, monitor and improve response strategies.

This research deals with the effect of Covid-19 on international tourism, and more specifically intends to forecast tourist arrivals from France, Germany and Italy to Greece, performing Error, Trent and Seasonality (ETS) forecasting to measure the impact of Covid-19 shock on future tourism demand until 2025.

Over the last decade, an average of 1.2 million tourists arrived in Greece from France, 2.7 million from Germany and 1.1 million from Italy, representing 71.2% of total EU arrivals for 2020. Besides, these countries from 2010 until the most recent publicly available data and international institutions, constitute 50% of the tourists that Greece attracts. Additionally, this study applies the augmented Dickey-Fuller (ADF) test, the Phillips–Perron (PP) test, and the Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test to assess the unit root hypothesis. The ADF and PP methods test the unit root hypothesis in the level values of tourist arrivals. Finally, the ETS forecasting model shows that in 2025 arrivals will be the same as in 2018, and tourism revenues will be reduced by 25 billion euros.