The impact of tourism on economic growth : a dynamic stochastic general equilibrium approach

Abstract

The academic community has studied the impact of tourism on economic growth since the 1990s. Scholars have advocated a tourism-led economic growth (TLEG) hypothesis using the case of Spain and found a significant positive correlation between international tourism and economic growth in most instances. However, most extant studies adopt an econometric approach. The reduced models used in this method lack explicit theoretical support and do not reflect the operating mechanisms of an economy. In other words, a positive correlation found using an econometric approach is insufficient to confirm that tourism leads to economic growth, and cannot explain the causalities among different variables. This study investigates the contribution of tourism to economic growth when there is a productivity shock in the tourism sector. The study uses Mauritius, Spain, New Zealand and the USA as sample destinations. To address the issue of asymmetric information in the employment market, a two-sector dynamic stochastic general equilibrium model is constructed that incorporates the search-matching theory. The model is estimated and simulated with actual tourism satellite account and economic data from the selected destinations using the Bayesian method. The main findings are as follows. First, a productivity improvement in the tourism sector can lead to economic growth in the selected destinations. Second, different sensitivities of international tourists to price changes influence the contribution of tourism development to economic growth. Third, the market structure in terms of domestic and international tourism output moderates the impact of tourism on economic growth. Last but not least, the tolerance of consumers for postponing consumption also affects the relationship between tourism and economic growth. This research expands the application of the dynamic stochastic general equilibrium model in tourism economics by introducing the search-matching theory to the modelling process and using the Bayesian method to estimate and simulate the model for the first time. From a practical perspective, the study will help destination governments and policy-makers to develop long-term tourism policies and strategies.