Factors affecting international tourist arrivals in Kenya

Abstract

Tourism is one of the most important industries in Kenya, being the major foreign exchange earner for the country. Moreover, the industry employs a considerable number of Kenya's work force and contributes immensely to Kenya's economy. Given the importance of the industry, the aim of the paper was to quantitatively ascertain the determinants of the demand for tourism. The study used OLS to estimate a log-linear single equation demand for tourist model. In the long-run, the results suggest that there is no relationship between the international tourist arrivals and aircraft accident as proxy for safety, number of reported crimes as proxy for security, cost of Jet fuel as proxy for transportation costs, GDP per capita income as proxy for tourist incomes, real exchange rate as proxy of tourism price of goods and services and political and civil unrest as well as terrorism attacks. This could be explained by the fact that increases in long-term prices and cost of tourism deter tourists, particularly "high budget" tourists. Using a log-linear single equation model, the empirical results show that in short-run the aircraft accident as a proxy of tourist safety and the real exchange rate as proxy of tourism prices for goods and services in the country relative to countries of tourist origin have significant influences on inbound tourism arrivals in the Kenya. The single-equation regression model presented in this paper show that international tourism demand by world tourist for Kenya is safety and cost/price inelastic. This is in the short-run, indicating that most holidays are not planned well in advance. This paper highlighted an empirical issue involving the estimation of demand models using non-stationary data. A clear message is a need to distinguish between spurious and cointegrating regressions. The single-equation regression model presented in this paper may be deceptive in suggesting that there exist no relationship between international tourism demand by world tourist for Kenya and tourist incomes, security, cost of transport and political and civil unrest as well as terrorism attacks. A more encompassing model like Almost Integrated Demand System in analysing the determinant of the tourism demand is needed. This will allow comparison of between different tourist destinations and relativity among tourist country of destination and origin. This would allow cointegration analysis and error correction modelling to uncover both long run and short run relationship among the determinants of the variables.