Peering Through the Fog of Uncertainty: Out-of-Sample Forecasts of Post-Pandemic Tourism

Serhan Cevik

No 2023/070, IMF Working Papers from International Monetary Fund

Abstract: This paper uses an augmented gravity model framework to investigate the historical impact of infectious diseases on international tourism and develops an out-of-sample prediction model. Using bilateral tourism flows among 38,184 pairs of countries during the period 1995–2017, I compare the forecasting performance of alternative specifications and estimation methods. These computations confirm the statistical and economic significance of infectious-disease episodes in forecasting international tourism flows. Including infectious diseases in the model improves forecast accuracy by an average of 4.5 percent and as much as 7 percent relative to the standard gravity model. The magnitude of these effects, however, is likely to be much greater in the case of COVID-19, which is a highly contagious virus that has spread fast throughout populations across the world.

Keywords: Infectious diseases; tourism flows; gravity model; predictability; out-of-sample forecasting; out-of-sample prediction model; forecasting performance; tourism flow; infectious-disease episode; Tourism; Gravity models; Communicable diseases (search for similar items in EconPapers)
Pages: 18
Date: 2023-03-17
New Economics Papers: this item is included in nep-tur
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Journal Article: Peering Through the Fog of Uncertainty: Out-of-Sample Forecasts of Post-Pandemic Tourism (2024)
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