Modelling the Determinants of International Tourism Demand in Cabo Verde Islands by European Countries: A Dynamic Panel Data Econometric Analysis

Abstract

Tourism in Cabo Verde is considered the engine of the country's economic growth, representing a significant weight in GDP, being the largest source of foreign exchange and the main export sector for services in the country. The purpose of this study was to identify and measure the impact of the main determinants of the inbound international tourism inflow. To achieve this, a panel data approach was used. The annual panel's data set includes the number of arrivals from the nine (9) European generating countries, published by INE in the period 2000 - 2018, and several possible explanatory variables. Taking into account the changing structure of consumer preferences, a dynamic model is estimated using the GMM-DIFF estimator. The results suggest that the international demand for tourism in Cabo Verde depends strongly on the evolution of economic activity in each of the issuing countries and is strongly influenced by the previous demand. The results also show that external shocks, such as economic and financial crises, negatively impact the demand for tourism in Cabo Verde. As policy measures, the study recommends diversifying the promotion of tourism to different countries, in order to limit vulnerability to changing economic conditions in a single region or specific economic bloc.

Keywords

• cabo verde
• dynamic panel data
• econometric model
• gmm estimators
• international tourism demand