Tourism is a major pillar of the Mauritian economy. According to estimates for 2010, the tourism industry has contributed Rs 39,456 million to the Mauritian economy and has provided direct employment to 27,161 workers. The contribution of tourism to GDP at basic price stands at 7.4% in 2010. This fact is indicative of the importance of the tourism sector to the Mauritian economy.
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To evaluate the impact of tourism on economic growth in Mauritius, a log-linear model will be estimated. However, economic growth may not be influenced only by tourism, but there are also other macro economic factors which may have an effect on growth. As such, these factors will be taken into consideration in the model. The model consists of standard variables such as Investment (INV), Exports (EXP) and Inflation (CPI), as well as one variable (TRP) which will be used to quantify the impact of tourism, such as tourism receipts. Real GDP per capita is used as a reference variable in order to demonstrate the impact of tourism on economic growth.
4.2 Types of Data
Primary data is collected on source and is not been subjected to processing or any other manipulation. The most common methods to collect primary data consist of surveys, interviews and focus groups. As such, primary research entails the use of immediate data and is collected by the researcher particularly to meet up the research objective of the subsisting project.
Making use of primary data implies that researchers are collecting information for the specific purposes of their study. As such, the questions the researchers ask are tailored to extract the data that will help them with their study. However, it is time consuming and costly to collect such data.
4.2.2 Secondary Data
Secondary data consists of pre-existing information which is not gathered for the purpose of the current research. Secondary data is readily available and inexpensive to obtain. In addition, such data can be examined over a longer period of time. Secondary data includes information from the census, a company’s financial position and safety records such as their injury rates, or other government statistical information such as the number of workers in different sectors.
In secondary data, information relates to a past period and as such, it lacks aptness and has unsatisfactory value. The drawback is that often the reliability, accuracy and integrity of the data is uncertain. However, it is easier to collect such data and longitudinal study may be possible.
4.3 Model Specification
A simple log-linear Cobb-Douglass production function is used to measure the impact of tourism on economic growth in Mauritius. The equation is as follows:
GDP = f (INV, TRP, CPI, EXP)
Consider the following model, known as an exponential regression model:
GDPt = β0 INVt β1 TRPt β2 CPIt β3 EXPt β4 e εt (4.2.1)
which may be expressed alternatively as
lnGDPt = lnβ0 + β1lnINVt + β2lnTRPt + β3lnCPIt + β4lnEXPt + εt (4.2.2)
where ln is the natural log (i.e log to the base e, and where e = 2.7183)
Equation 4.2.2 can be written as:
lnGDPt = C + β1lnINVt + β2lnTRPt + β3lnCPIt + β4lnEXPt + εt (4.2.3)
where C = lnβ0
Therefore, the transformed model is:
ln GDPt = C + β1 ln INVt + β2 ln TRPt + β3 ln CPIt + β4 ln EXPt + εt
Where ln GDP: Log of real gross domestic product per capita
ln INV : Log of investment
ln TRP : Log of tourism receipts per capita
ln CPI : Log of consumer price index used as a proxy for inflation
ln EXP : Log of exports
C : Constant term
εt : White noise disturbance term
In the above log-linear model, the dependent variable, GDP, is expressed as a linear function of four other independent variables, also known as the explanatory variables, namely INV, TRP, CPI and EXP. It is often assumed for such log-linear model that the causal relationships which may exist, flow only in one direction, namely from the explanatory variables to the dependent variable.
The parameters of the model can be estimated by using the Ordinary Least Squar