Investigating the non-linear impacts of seven types of natural disasters on inbound tourism: Insights from the EM-DAT database

Abstract

The growing frequency and intensity of disasters due to climate change present considerable risks for tourist destinations, necessitating comprehensive research on their economic impacts. This study investigates the contemporaneous dose-response relationship between natural disasters and inbound tourism by estimating a flexible binned regression model. The analysis is conducted in a panel data setting from 1995 to 2019, spanning over 150 countries and accounting for the impact of more than 8,300 individual disasters from seven distinct categories. Examining seven natural disaster types (earthquakes, epidemics, extreme temperature events, floods, landslides, storms and wildfires) and five disaster impact metrics reflecting their human and economic impacts, the analysis reveals that increased disaster impact, except for earthquakes, correlates with reduced levels of tourist arrivals and travel expenditure. The paper provides valuable insights into the relationship between disasters, climate change, and tourism economics, informing disaster mitigation strategies and broader climate change assessments for tourism sector policy and decision-makers.