The own price of tourism is another variable that has been found to have an important role to play in determining the demand for international tourism. In theory this variable should contain the travel cost to the destination, but another important component in selecting destinations is the cost of living for tourists at these destinations. The cost of living for the tourist should be considered as the price of complementary goods. Notably, due to difficulties in obtaining data, travel costs have been omitted in most of the studies, Dritsakis (2004) and Lim and McAleer (2002) are some of the exceptions. International tourism demand tends to follow the law of demand. An increase in tourism prices tends to reduce international tourism demand.
Price elasticities of demand for tourism have been found by a number of scholars to be less than a unit in absolute value and relatively inelastic (Divisekera, 2003; White, 1985).
Giacomelli (2006c) points out that demand for Mediterranean tourism has low price elasticity (0.32) while a 1 per cent increase in destination infrastructure would lead to 0.14 per cent increase in tourism arrival. Using structural time series models in the state space function estimated by prediction error decomposition, Gonzalez and Moral (1996) find that sensitivity of Spanish market is high for changes in relative price.
In empirical work, prices of tourist goods can be represented by the tourist price index or Consumer Price Index (CPI). Many scholars for example, Lim, 1997 and Crouch, 1994
UNIVERSITY OF IBADAN
support the use of the tourist price index. However, most studies use the CPI since many countries do not compute the tourist price index. Martin and Witt (1988) do not find sufficient differences in the explanatory power of the tourist price index over the CPI. Thus, the tourist price index and CPI can be used interchangeably. As the price of substitute goods, tourism studies have used relative prices between different country destinations. According to Song and Witt (2006) there are two different forms of substitute prices between country destinations that have been used: One allows for the substitution between the destination and a number of competing destinations separately, and the other calculates the cost of tourism in the destination under consideration relative to a weighted average cost of living in various competing destinations, and this index is adjusted by relevant exchange rates. The weight is the relative market share (arrivals or expenditures) of each competing destination.
In the absence of a comprehensive tourism price index, Worrell et al (1997) approximate visitor costs by dividing tourism receipts by the number of bed nights. They find that tourism prices in Barbados as well as relative prices had significant impacts. Gil-Pareja et al (2007) use the relative purchasing power parity (RPPP) as a proxy for tourism costs that take account of variations in the exchange rates between source and destination, and observe that an increase of 1per cent in the relative prices in the destination decreases tourism demand by 0.36per cent.
Bashagi and Muchapondwa (2009) find that the local tourism price elasticity is -3.7, meaning that a 1 per cent decrease in tourism prices in Tanzania is associated with an increase of more than 3 per cent in international tourist arrivals to the country. The tourism prices of the alternative destination had no significant impact in explaining the international tourism demand in Tanzania. Thus, they recommend that the Tanzanian government must maintain macroeconomic stability, especially low inflation, in order to reap the full economic benefits from international tourism. Narayan (2004) estimated an ARDL model of international
UNIVERSITY OF IBADAN
(complementary destination) in all countries except Singapore, Thailand and UK. For example, a 1per cent increase in price of goods and services in China, Indonesia, Singapore, Thailand and Hong Kong would lead to a 1.03per cent increase of UK tourists. In addition, a 1per cent increase in price of goods and services in Malaysia leads to 0.98per cent and 1.04per cent decrease in tourist arrivals to Malaysia from UK and US respectively. Walle (2010) finds that a 100per cent increase in the Ethiopia‟s CPI to Kenya‟s CPI leads to a 44per cent decrease in the number of tourist arrivals in Ethiopia. This is in line with the expectation that as Ethiopia becomes an expensive tourist destination relative to Kenya, many tourists who have decided to visit East Africa would prefer Kenya to Ethiopia.
Some authors adjust the price measure by the exchange rate while some include exchange rate as a separate variable. The exchange rate is defined as the number of units of the local currency which can be exchanged for a unit of the foreign currency. The change in the exchange rate affects the relative values of the currencies in question (Lim, 2004), hence changes in the exchange rate will lead to either an appreciation or depreciation of the tourist‟s currency. Appreciation of the tourist‟s currency will encourage more tourists to travel there while depreciation will discourage them from visiting. Another factor that contributes to the cost of living is the exchange rate between the origin country and the destination country currencies. The exchange rate currency has been used in different forms: for instance, Qiu and Zhang (1995) use the exchange rate currency separately from the CPI to account for the cost of tourism. Song and Witt (2006) used the CPI of destination country divided by the CPI in the origin country and adjusted by the appropriate exchange rates.
According to Shamsuddin (1995), for example, exchange rate elasticities only vary between -.78 and 1.27 in Malaysia. In Turkey, they vary from .18 to 4.22 based on dependent variables of expenditure estimates for arriving tourists (Uysal and Crompton, 1985). Some models used the tourist price index (or CPI) adjusted for the exchange rate, while others separated the tourist price index or CPI and exchange rate. The decision to treat the exchange rate separately is based on the assumption that the international tourist has more up-to-date information about the exchange rate than about prices of commodities in the destination country (Webber, 2001). Bashagi and Muchapondwa (2009) observe that the international tourism demand elasticity with respect to the exchange rate is almost 3 per cent, suggesting that a weaker Tanzanian shilling raises international tourism demand for the country, as the country will be seen as a source of cheaper tourism experiences.
UNIVERSITY OF IBADAN
Tourism prices also include transport costs, the cost of accessing tourism facilities and the cost of commodities consumed by tourists while on tour. Though theoretically important, the transport cost variable has usually played a minor role in demand models. It has often been omitted from models because previous researchers have found it to be insignificant. Also, there exists no clear and accurate proxy for representing the costs of transport. Jud and Joseph (1974), stress that previous researches have shown a strong negative correlation between the level of income and the cost of travel. As a result, such studies have been unable to separate the independent effects of income and travel costs upon the demand for travel. Gray (1966) finds the transportation cost variable to be statistically insignificant in explaining the travel spending abroad and fare payments to foreign flag carriers by Canadian and US residents.
Bankole and Babatunde (2010a, 2010b) conclude that total tourist arrivals into Nigeria are related to transportation cost.
Transport costs usually are treated separately from the price of tourist goods and services.
The demand for transportation in international travel is a derived demand, as it is the consumer who has to be transported to the destination (Lim 1997). About 58 per cent of the studies examined by Crouch (1994) used the cost of transportation as an explanatory variable.
Transportation costs are measured by either the airfare for air travel, or fuel prices for surface travel. According to Lim (1997), since oil price is the main determinant of road and airfares, oil prices can be used to represent transport costs.
Bashagi and Muchapondwa (2009) posit that in the long run, it is largely the local tourism prices, tourist income, transport cost and the exchange rate that immensely affect international tourist arrivals in Tanzania. One per cent decrease in transport costs increases the number of international tourist arrivals by about 0.3 per cent.
UNIVERSITY OF IBADAN
Boopen (2006) obserces that transport infrastructure is an important element of the tourism equation. One per cent increase in transport capital will increase the number of tourist arrivals by 0.127per cent in the short run and 0.17 per cent in the long run. He however notes that non-public transportation capital, though having a positive sign, has an insignificant effect in both runs.