Authors

Carmela Coppola

Document Type

Dissertation

Abstract

Increasing weather variability around the world has led to many researchers examining the impacts of weather variability on vulnerable industries. For example, the tourism industry can make up a large portion of an economy’s growth, with some of the most dependent countries relying on tourism for over 40% of GDP (World Travel & Tourism Council 2014). In an attempt to better understand the relationship between weather variability and the tourism industry at the country level, this study employs a series of fixed effects panel regression models to analyze the impact of rainfall and temperature on tourism levels and growth rates among 194 countries. Variations of the model allow for the exploration of the differential impacts sustained by island and non-island countries to help determine whether island countries are more vulnerable to weather variations due to the large contribution of tourism to their economies (Uyarra et al. 2005). Results suggest that using a yearly average measure of the temperature and rainfall data does not yield useful results, while using seasonal temperature and seasonal rainfall averages appears to explain the different impacts across island and non-island countries with more consistency.