| dc.description.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. | en |
