Using the panel cointegration approach to analyse the determinants of tourism demand in South Africa

Estimating tourism demand has become a challenge among researchers, as identification of key determinants is important for policymakers at a time when tourism has become the world's largest industry. Using a theoretical framework based on the gravity model, this paper models inbound tourism demand for South Africa to estimate price and income sensitivities as well as the impact of other important factors that affect tourist flows, such as the location of markets and socio-political factors. Given the non-stationary but cointegrated nature of the panel data, panel cointegration estimation techniques are employed. The results show that tourists are sensitive to price changes in South Africa and also to tourism price changes in competing destinations. The level of development, tourism infrastructure, distance (or transportation costs), common border and language are also found to affect arrivals. The results also indicate the need to conduct estimation by regional groupings for a better understanding of different markets