Impact of Tourism of Economic Growth in Mauritius


The worldwide prospects of the tourism industry over the long term are bright. Recent forecasts from the World Tourism Organisation have shown that the number of international tourist arrivals is likely to increase to 1.6 billion by 2020. International tourism is likely to become one of the most significant generators of foreign exchange for many tourism destinations in the world and as such, it will account for a larger share of employment. The tourism industry is undoubtedly an important pillar of the Mauritian economy. The Government expects to attract 2 million tourists annually by 2015. Our country has a very high level of positioning in the international tourist markets and the hotels are recognised for their high standards and the quality of services provided. Certain empirical studies have shown that tourism has a positive impact on the Mauritian economy in terms of employment creation, contribution to government revenues, foreign exchange earnings, contribution to national income and investment stimulation.

Given the significance of the tourism industry for the Mauritian economy, the aim of this paper is to analyse the impact of tourism on economic growth in Mauritius over the period 1976 to 2009. Time series analysis has been carried out to test the relationship between growth rate and tourism receipts. Real GDP per capita has been used as the response variable to measure the impact of tourism on economic growth; and the model also includes other variables such as investment, inflation and exports. The results show that there exists a positive and significant relationship between the measure of economic growth and tourism receipts. Thus, tourism has become a major determinant of economic growth for Mauritius and the industry is called upon to become more dynamic or even the main pillar of the economy.


The past three decades have witnessed a drastic change in the economic structure of Mauritius. Our country has changed from being a low-income economy dependent mainly on agriculture and textile to that of a diversified middle-income economy. Mauritius has been able to achieve this economic growth mainly due to the development of the tourism industry. The Mauritian economy is one of the most successful in Africa. With the expiry of the Multifibre Agreement and Sugar Protocol, which provided preferential access to Mauritian products in overseas markets, the tourism industry gained in prominence. The Government has elaborated policy not only aimed at promoting elite tourism, but also to provide facilities for low-budget tourism.

The impact of tourism on economic growth has been of interest to many academics and policy makers. As such, it is also an important issue for Mauritius as tourism is a fast expanding sector, bringing along economic benefits such as employment creation and generation of foreign exchange. Mauritius had about 70,000 visitors in 1970. Between 1985 and 2000, tourism arrivals increased from 148,860 to 656,453 and the sector grew by approximately 340%. In 2010 , tourism arrivals were approximately 934,827 and 27,161 persons were employed in the industry. The tourism sector in Mauritius is mainly dependent on the European market, particularly France and the United Kingdom. The contribution of the tourism industry towards GDP has been on the rising trend, with an approximate share of 7.4% in 2010, while tourism receipts amounted to 39.5 billion rupees.

Mauritius has embarked on a new economic path which is paved by the development and strengthening of the tourism sector. Together with the incentives provided by the Government which have countless effects on the promotion of that sector, the crucial role played by the aviation sector has helped to boost the tourism industry. The local authorities aim to attract 2 million tourists in 2015 . As such, this sector is called upon to grow significantly in the coming years, averaging a 15% growth each year.


What is Tourism?

Tourism can be considered as travel for recreational, leisure or business purposes. It is defined by the World Tourism Organisation (UNWTO) as “people who travel to and stay in places outside their usual environment for more than twenty-four hours and not more than one consecutive year for leisure, business and other purposes not related to the exercise of an activity remunerated from within the place visited." Tourism has become a popular global leisure activity, whereby in 2008 over 922 million international tourist arrivals were recorded, with a growth of 1.9% as compared to 2007. International tourism generated US$ 852 billion in 2009 and the UNWTO states that international tourist arrivals might have grown by 4% in 2010

Mathieson and Wall (1982) defined tourism as "the temporary movement of people to destinations outside their normal places of work and residence, the activities undertaken during their stay in those destinations, and the facilities created to cater to their needs", while according to Macintosh and Goeldner (1986) tourism is "the sum of the phenomena and relationships arising from the interaction of tourists, business suppliers, host governments and host communities in the process of attracting and hosting these tourists and other visitors."

Tourism is central for many countries, such as Egypt, Greece, Lebanon, Spain and Thailand, and many island nations, such as The Bahamas, Fiji, Maldives, Seychelles and Mauritius, because of the large intake of money for businesses and the opportunity for employment in the service industries associated with tourism.

Economic Impact of Tourism | Stimulating economic growth

According to Eadington and Redman (1991), tourism can play an important role in stimulating economic growth and it may be of particular significance to countries that do not possess major supplies of natural resources. They found that in countries such as Jordan, Ireland, the Caribbean, and to a lesser extent Egypt, income from tourism has contributed significantly to economic development. They also argue that for countries such as Cambodia, tourism may be a major source of revenue for future economic development. The fact that tourism is a major source of foreign exchange is of particular significance and as such, it provides the basis for export-led economic growth.

It must also be noted that the development of tourism may reduce a country’s dependence on primary commodities as a source of export earnings. However, Brown (1998) claimed that over-dependence on a single source of income is always likely to create risks, but these are probably particularly apparent in relation to primary commodities where prices can display high levels of volatility year-on-year and where agricultural support policies operated in many developed economies have artificially depressed world market prices.

Generation of income

Sinclair and Stabler (1998) mentioned that a significant proportion of income may be generated from tourism expenditure and the impact of such expenditure may be considered under three headings:

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The direct effects arise from expenditure by tourists, which in turn generates income for businesses and households and revenue from taxation. Indirect effects arise as initial income received by households, government and local businesses is re-spent on activities necessary to provide the products and services purchased by tourists. This is sometimes referred to as ‘upstream’ expenditure’. Moreover, some of the income received by governments, households and businesses will be re-spent ‘downstream’, that is on consumption goods and services unrelated to the supply of tourism products. Some income will also be spent on their own consumption by households, governments and businesses, and this additional consumption expenditure is effectively being induced by the additional income received from tourism. Such consumption expenditure immediately provides a source of income for other households, for government and for business.

Sinclair and Stabler (1998) claimed that at each stage some tourism expenditure is lost because it is used to purchase imported goods and services and some induced expenditure may be lost through savings. Such losses can either be in the form of import leakages or export leakages. Import leakage occurs when tourists demand standard of equipment, food and other products that the host country cannot supply. For many developing countries, much of the income from tourism expenditure leaves the country to pay for those imports. Export leakage, on the other hand, occurs when multinational corporations or foreign businesses, which have the necessary capital to invest in the construction of tourism infrastructure and facilities, take their profits back to their country of origin.

Sinclair (1999) and Bezmen (2006) argued that the contribution of tourism to income of a country is improved by a phenomenon known as the ‘Tourism Income Multiplier’. This is due to the fact that money spent by tourists will be re-spent by the recipients.

Tourism Income Multiplier (TIM) = 1/Proportionofleakages

In case there is a high proportion of a leakage in the economy, the multiplier will be low and the country will not benefit greatly from tourism while if the economy can minimize the leakages, then the contribution of tourism will be higher.

Employment creation

According to the UNWTO, the tourism industry which continues to be amongst the most dynamic economic sectors, is a reliable tool for sustainable job creation. Given it is a service industry, it is generally argued that tourism is mostly labour intensive in nature and one of the major economic impact of tourism is that it is an engine for employment creation. According to Mathieson and Wall (1982), such employment may be classified into 3 categories:

Direct employment occurs as a result of tourism expenditure, for example those persons employed in hotels, restaurants or by tour operators. Indirect employment relates to job opportunities for those persons supplying the goods and services related to tourism, such as wholesaler, fishermen, retailers, vegetable sellers, taxi drivers and farmers. Induced employment arises from spending by local residents of tourism income. For example when those employed in hotels spend money on purchase of goods and services, this will in turn generate new employment opportunities. The tourism industry demands all grades of workers, ranging from unskilled to highly skilled and since it is a growing and dynamic industry, it will remain a major contributor to employment creation.

Contribution to government revenues and foreign exchange

According to Ennew (2003), tourism earnings can be considered as a major source of revenue, particularly for developing countries such as Mauritius, Maldives and Seychelles, whereby such revenues may help government to finance part of their development efforts. Government revenues from the tourism industry may be classified as direct and indirect contribution. Direct contribution includes taxes imposed on incomes from tourism employment or on tourism business and direct levies on tourists such as departure tax while indirect contribution concerns taxes and duties imposed on goods and services supplied to tourists. Tourism also brings foreign exchange to a country, especially tourists travelling from hard currency countries and who spend their Euro, US Dollar or Yen within the host country.

Development of new business

Douglas and Derret (2001) mentioned that tourism may also encourage entrepreneurship and the development of new small businesses, particularly among groups who might not have easy access to formal labour markets. Special interest tourism, due to its relatively early stage of development is thought to be particularly conducive to entrepreneurial activity. The entrepreneurial activity may range from specialised tour and guiding services to new types of attraction and to the provision of local handicrafts.

Costs and Benefits associated with Tourism


There are many hidden costs to tourism which can have unfavorable effects on the host country

Economic Costs

There are significant economic costs associated with tourism development. At such, if resources are being used for the development of tourism they cannot be used in other sectors of the economy; if labour is employed in tourism, it is not available for use by other sectors of the economy and if capital is invested in tourism, it cannot be invested in other projects. Consequently, there is a danger that tourism may ‘crowd-out’ development in other sectors. This can be significant if an economy is at full employment and there are no unused resources available. However if resources particularly labour used in tourism are not used most efficiently, then productivity growth will tend to be rather low. The general tendency of tourism to create primarily low skill, part-time, seasonal jobs is often cited as a negative dimension in relation to the sector’s capacity to generate employment (Townsend, 1997).

Tourism development also imposes some significant and direct financial costs on governments, which include the costs of advertising and marketing the country as a destination and the establishment and operation of national tourism organisations as well as the costs associated with developing and maintaining relevant infrastructure, airport expansion and money spent in road improvement. Additional costs may be incurred in instances where governments need to provide subsidies and other incentives to attract private sector investment (Wood, 1996).

In case tourism development relies heavily on imported goods and services, there is a risk that existing local production may be displaced or its development may be halted. This is particularly significant if ‘demonstration effects’ result in the local population copying tourists and increasing their consumption of imported goods and services rather than domestically produced ones.

Environmental Costs

Tourism may endanger natural resources such as beaches and coral reefs or historical sites and may also increase litter, noise, and pollution. Tourism also increases competition for limited resources such as water and land, as such, this may result in land degradation, loss of wildlife habitats and deterioration of scenery.

Socio-Cultural Costs

Tourism may attract visitors whose lifestyles and ideas conflict with the community's. Such visitors may consume drugs or alcohol. It can alter individual behaviour and family relationships. Tourism may lead to amplification of sexually transmitted diseases and to deterioration of traditional values and culture through imitation of visitor behaviour. It can also involve violations of human rights, whereby people may be dislodged from their land and beaches may be restricted for hotel guests while access is barred to local people.

Seasonal character of jobs

Given the seasonal character of the tourism industry, it may create economic problems particularly for countries which are heavily dependent on it. Seasonal workers may face problems such as job insecurity, with no guarantee of being employed in the next seasons, poor working conditions and unsatisfactory employment related benefits.


The tourism industry also brings substantial benefits to the host country.

Economic Benefits

Tourism helps diversify and stabilise the local economy and it also enables governments to raise extra tax revenues each year through accommodation and restaurant taxes, airport taxes, sales taxes, park entrance fees and employee income tax. Tourism helps create local jobs and business opportunities. Tourism also stimulates investment as growth of worldwide tourism can encourage multinationals from developed countries to invest in the tourism sector of developing countries. Tourism can also act as a tool for infrastructure investment stimulation as it can induce government to make infrastructure improvement such as better water and sewage systems, roads, electricity and public transport networks which in turn can improve quality of life for residents as well as facilitating tourism.

Environmental Benefits

Tourism encourages conservation and preservation of natural, cultural and historical resources and furthers community beautification and revitalisation. As the environment is a basic component of the tourism industry’s asset, revenue from that industry is often injected in the development and maintenance of protected areas or other tourist attractions.

Socio-Cultural Benefits

Godfrey and Clarke (2000) mentioned that socio-cultural benefits of tourism relates to changes in local quality of life and sense of place. Tourism brings in foreign currencies to finance community facilities and services that otherwise might not be developed. It encourages civic involvement and pride and provides cultural exchange between hosts and guests. It also fosters the celebration of local festivals and cultural events. Tourism encourages the learning of new languages and skills.

Regional Development

Tourism can also impact positively on regional development, whereby it may help to reduce some of the inequalities between different parts of a given country. Regions which are deprived of other major resources or do not have major urban centres may be able to use tourism to improve regional incomes and reduce out-migration. According to Pearce (1995) and Weaver & Fennell (1997), skiing, various forms of rural tourism, some forms of eco-tourism and of course, sun, sand and sea tourism have all been used to promote the development of peripheral regions in both developed and developing countries. In developed economies, tourism also has the potential to stimulate economic regeneration, as the experience of cities such as Manchester in the UK and Bilbao in Spain has shown (Plaza, 2000).

2.2 Empirical Review

2. 2.1 Models to evaluate the Economic Impact of Tourism

Keynesian Multiplier

Traditionally tourism impact analysis relied heavily on simple Keynesian multipliers. The real benefit from tourism is not the actual expenditure by tourists, but rather the final impact that this expenditure has on the economy. Different multiplier values can be calculated depending on the outcome which is of interest. As such, output multipliers measure the impact of tourism expenditure on the output of an economy; income multipliers measure the impact on income and employment multipliers measure the impact on employment.

According to Cooper et al (1998), Keynesian multipliers only give a rather limited and partial perspective on the impact of tourism, as they focus on simple aggregates and are unable to address the nature of linkages between sectors. Input-Output Model

Input-Output analysis relies on the data contained in input-output tables and analyses the effects of tourism by charting the movement of initial tourism expenditure through different sectors of the economy. One of the major strengths of this analysis is its ability to measure direct, indirect and induced effects. Archer and Fletcher (1996) use input-output analysis to evaluate the impact on the Seychelles of tourists from a range of different destinations. Such analysis also requires detailed data on tourist expenditures as well as data on inter-sectoral transactions. Input-Output analysis can be a costly exercise but it offers significant benefits in terms of understanding tourism impacts.

Input-Output analysis also has certain limitations even if can provide a much greater understanding of the linkages across and the relationships between different sectors as well as the overall contribution of tourism. Such analysis is generally classified as an inflexible approach to general equilibrium modelling because it does not allow for factor substitution between sectors and prices are taken as given (Zhou, 1997). In particular, it assumes that wages and prices do not change when tourism expenditure changes. In reality, a change in tourism expenditure is likely to change both output and prices-if there is a significant increase in expenditure for example, then businesses will experience an increase in demand which means that prices might be expected to rise and also wages. As such, resources will be attracted into the sector to enable production to increase.

Computable General Equilibrium Model

The Computable General Equilibrium (CGE) modelling enables economists to analyse the impact of tourism in an alternative way. It has the same ability as input-output analysis to highlight the inter-sectoral linkages without being restricted to fixed prices and wages. In addition CGE modelling can simulate the impacts on tourism of different policy changes.

Zhou et al (1997) noted that the negative consequences of a decline in tourism expenditure in Hawaii were predicted to be much greater using input-output analysis than using CGE analysis. This difference occurs because the CGE model is able to reallocate factors of production and adjust prices to accommodate the reduction in tourist demand. In addition to greater accuracy in estimation, CGE models may also provide a greater understanding of the nature of the impact of external shocks and policy changes.

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2.2.2 Empirical Literature

Empirical literature has shown that tourism contributed to export-led economic growth. Dritsakis (2004) showed, in a study on the economic growth performance of Greece, that tourism has a long-run economic growth effect, while Balaguer and Cantavella-Jorda (2002) using Spain’s economic data, confirmed the validity of tourism-led growth hypothesis for long-run economic performance. Tosun (1999) and Guduz and Hatemi (2005) for Turkey and Oh (2005) for Korea, have also found evidence to substantiate the tourism-led growth hypothesis.

An increasing amount of literature has been analysing the relationship and causality between tourism and economic growth rate, both in specific countries (Durbarry, 2004 for Mauritius or Balaguer, J. and Cantavella-Jorda, 2002 for Spain) or in broader samples (Eugenio-Martin, Morales and Scarpa, 2004 for Latin America). Time-series was used for Mauritius and Spain, while a dynamic panel data method estimator was used for Latin America. Balaguer and Cantavella-Jorda (2002) constructed a model, which includes the real gross domestic product, international tourism receipts in real terms, and the real effective exchange rate. Their study shows that international tourism earnings affect positively the Spanish economic growth and there exists a long-run stable relationship between economic growth and tourism expansion.

Having conducted an analysis on a single country basis, Balaguer and Cantavella-Jorda (2002) on Spanish tourism and Oh (2005) on Korean tourism found that the increase in tourism income impacts on economic growth. Moreover, the studies by Dristakis (2004) on Greece and Durbarry (2004) on Mauritius empirically showed the existence of a bi-directional relationship between the two variables. It has also been found that studies which used panel data method gave similar results. Eugenio-Martin and Morales (2004), who analysed the relationship between tourism and economic growth for Latin American countries for the period 1985 to 1998 with an analysis based on a panel data approach, found that the growth in the number of tourists per capita resulted in a positive effect on the economic growth of the countries which have low and medium levels of income per capita, but not in the group of rich countries. This may lead to conclude that the increase in tourism arrivals in a country offers a prospect for economic growth while countries are developing, but not when countries are already developed.

In their analysis among 32 selected countries including both OECD countries and non-OECD countries, C.C. Leea, C.P. Chang (2008) concluded that there is a unidirectional relationship running from tourism towards growth for OECD countries whereas a bidirectional causality relationship exists for non-OECD countries.

Brau, Lanza, and Pigliaru (2003) who compared the relative growth performance of 14 “tourism countries” within a sample of 143 countries, noticed that tourism countries grow faster than all the other sub-groups (OECD, Oil Exporting, LDC, Small). Many developing countries now believe that tourism is an important and integral part of their economic growth and development strategies as it serves as a source of scarce financial resources, job creation, foreign exchange earnings, and technical assistance (Sinclair, 1998 and Dieke, 2004).

The test done by Brau, Lanza and Pigliaru (2003) for a broad cross-section of countries is not robust to the possible existence of endogeneity of tourism. Tourism may be associated with human capital, geographic or cultural features, but may not be an independent determinant of growth. Thus tourism can possibly foster growth within countries, demanding for qualified labour force or promoting competitiveness but it may not be able to explain differences in growth patterns between countries; that may derive from other explanatory factors.

An important study on the impact of tourism on economic development has been carried out by Proenca and Soukiazis (2005), who used the convergence approach based on Barro and Sala-i-Martin (1992) type analysis. They examined the impact of tourism on the per capita income growth of Portuguese regions and concluded that tourism can be considered as an alternative solution for enhancing regional growth in Portugal, if the supply characteristics of this sector are improved. In their investigation, they estimated the correlation between the bed capacity of Portuguese regions and the regional economic growth measured by GDP per capita growth. They concluded that 1% increase in accommodation capacity in tourism sector stimulated 0.01% increase in per capita income. Tourism also furthers the convergence rate of per capita income in Portuguese regions.

Lanza and Pigliaru (1999), employing a different methodology, examined the tourist specialisation of the country and its effect on the economic growth using the Lucas’s two-sector endogenous growth model. They found that countries with endowments of suitable natural resources large relative to the size of their labour force are likely to acquire a comparative advantage in tourism and will grow faster as compared to those who specialise in the manufacturing sector.

Brau et al. (2003) further analysed the correlation between the tourism specialisation of the country (the ratio between international tourism receipts and GDP at market prices) and the real per capita GDP growth rate. They noticed that small tourism countries had a tendency to grow faster during the period 1980-1995 than countries from OECD, oil producers, least developed countries or other small economies, and concluded that although smallness of a country is unfavorable to growth, the opposite is true if it is combined with tourist specialisation.


3.1 The Tourism Sector in Mauritius

During the last decades, Mauritius has evolved from a low-income economy heavily dependent on agriculture to a middle-income diversified economy. Such economic growth has been the result of an unprecedented boom in the tourism industry. The policy of the government is not only to promote elite tourism but also low budget tourism. The success of Mauritius as a high quality tourist destination is mainly due to its natural beauty, friendly and welcoming people, luxurious hotels with good amenities, improved air access, well targeted promotional campaign and effective marketing strategies and government support to the industry.

There has been a consistent growth in tourist arrivals over the last decades with the number of international tourist arrivals increasing from 72,915 in 1974 to more than 934,827 in 2010, according to figures obtained from the Central Statistical Office. The tourism sector which has become one of the most dynamic sectors, is expected to take an important place in the Mauritian economy. The objective of the government is to increase the level of annual tourist arrival to two million by 2015. As such it has implemented certain strategies which include opening of the sky, marketing plan to develop new markets, launching on numerous Integrated Resort Schemes and promoting the construction of new hotels.

3.2 Trend Analysis

3.2.1 Tourist Arrivals

Tourist arrivals in Mauritius have risen significantly from 72,915 in 1974 to 871,356 in 2009. Such rapid rate of increase positions Mauritius as one of the fastest growing tourism destination in the world.

During the period 1974 to 1979, arrivals nearly doubled, reaching a total of 128,360 in 1979. However, this was followed by a sudden decrease whereby total arrivals fell to 118,360 in 1983. This was mainly due to the oil crisis of 1979 which had a severe impact on the global economy with general economic recession and increased air fares.

From 1983 there was a consistent increase in arrivals and this was the result of the recovery of the world economy. In 1991, Mauritius experienced a low growth rate of 3.6% in tourist arrivals and this could be attributed to the fierce competition from Asian and Caribbean tourism destination and to economic recession. In 2000, Mauritius experienced a growth rate of 13.6% in tourist arrivals, which could be contrasted with that of 0.6% in 2001. This was mainly due to the adverse external shock of the terrorism attack of the 11th September 2001. For the following years, arrivals constantly increased, reaching a peak of 930,456 in 2008.

Tourist arrivals for the year 2009 declined by 6.4% to reach 871,356 compared to 930,456 for 2008. For the first nine months of 2010, the number of tourists visiting Mauritius increased by 6.2% to reach 646,656 as opposed to 608,885 for the same period of 2009. Excluding April 2010, all the other eight months for the period January to September 2010 experienced rises in the number of tourist arrivals when compared to the corresponding months of 2009. Tourist arrivals for 2010 were approximately 934,827, representing an increase of 7.3% over 2009 and in 2011, arrivals are forecasted to be around 980,000 representing an increase of 4.8% over 2010.

3.2.2 Market Trends

The major tourist generating countries are France, UK, Reunion Island and South Africa. Arrivals from Europe, which accounted for 66.5% of total tourist arrivals, decreased by 4.7% to reach 579,509 in 2009 against 608,358 for 2008. Arrivals from France, the leading market, representing 31.6% of total tourist arrivals and 47.6% of the European market, increased by 6.0% to attain 275,599 in 2009. However, for the period 2008 to 2009, falls in arrivals were recorded for the other major generating countries: United Kingdom (-5.5%), Italy (-14.6%) and Germany (-16.6%). For European countries, there has been a decrease in arrivals: Switzerland (-4.3%), Netherlands (-8.7%), Austria (-9.7%), Commonwealth of Independent States (-11.1%), Belgium (-13.1%), Spain (-20.4%) and Sweden (-39.1%).

In 2009, arrivals from Africa, which accounts for a share of 23.4% of total tourist arrivals, contracted by 4.5% to 204,308. The number of tourists Reunion Island increased by 9.1% to reach 104,946, while those from Republic of South Africa fell by 12.2% , amounting to 74,176.

Tourist arrivals from the Asian market in 2009, which represented 7.1% of total tourist arrivals, went down by 14.6% to reach 62,131. Arrivals from India, the major source on this continent, have declined by 10.6% to reach 39,252. A decrease in the number of tourists was noted from other Asian countries were as follows: Singapore (-5.7%), People's Republic of China (-17.8%), Japan (-22.8%), Malaysia (-22.9%), United Arab Emirates (-23.6%) and Hong Kong (-40.4%). Arrivals from Oceania went down by 44.7% from 20,161 to 11,143 due to declines in arrivals of 45.0% from Australia and 40.4% from the other Oceanian countries.

The number of tourists from top ten markets made up for 84.9% of tourists visiting Mauritius during the first nine months of 2010 as opposed to 84.4% for the same period in 2009. During the first nine months of 2010, tourist arrivals from Europe reached 414,787, while arrivals from France, the leading market representing 31.0% of total tourist arrivals and 48.3% of the European market, amounted to 200,151 during this period. Arrivals from Africa, with a share of 24.5% of total tourist arrivals, amounted to 158,223. The number of tourists from Reunion Island, the major market in Africa, was 81,052 and those from Republic of South Africa increased amounted to 56,590. The number of tourists from India amounted to 36,255.

3.2.3 Employment Creation

The tourism industry continues to be amongst the most dynamic economic sectors and is a reliable tool for sustainable job creation. Tourism is mostly labour-intensive in nature and one of the most important economic impacts of tourism is that it is an engine for employment creation.

According to the Survey of Employment and Earnings, direct employment in hotels, restaurants and travel and tourism establishments employing 10 persons or more was 27,161 at the end of March 2010 constituting a rise of 0.6% over the figure of 27,002 for March 2009. Of this number, 20,847 or 76.8% were engaged in hotels. During the recent years, there has been an increase in the number of people employed in hotels, whereby it increased from 19,536 in 2006 to 20,847 in 2010. This is mainly due to the fact that there has been an increase in the number of hotels in Mauritius./p>

3.2.4 Tourism Contribution towards Gross Domestic Product

The National Accounts Aggregates use statistics for Hotels and Restaurants as a proxy to identify the contribution of tourism to Gross Domestic Product (GDP). The table below summarises GDP by group as a proportion of total GDP in the economy.

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Table 3.2.4: Contribution of Tourism to GDP







Total GDP at basic
prices (Rs Million)







Hotels and restaurants
(Rs Million)







% Distribution of GDP
at basic price







Contribution of Hotels
and restaurants to
GDP Growth







The contribution of tourism to GDP at basic prices has risen from7.4% in 2004 to 8.6% in 2008. However, there was a slight fall in 2009. Nevertheless the tourism industry has emerged as one of the fastest growing productive sectors in Mauritius. This can be contrasted with other sectors like textile and agriculture, which have contributed 5.4% and 4.3% respectively to GDP in 2009. The contribution of tourism has increased to 7.4% in 2010 and as such the tourism sector positions itself as one of the main pillars of the Mauritian economy.


4.1 Introduction

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.

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

4.2.1 Primary 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:


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


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 Square method, if the assumptions of the classical linear regression model are fulfilled. As such,

GDPt* = C + β1 INVt* + β2 TRPt* + β3 CPIt* + β4 EXPt* + εt

where GDPt* = ln GDPt, INVt* = ln INVt, TRPt* = ln TRPt, CPIt* = ln CPIt, EXPt* = ln EXPt

The coefficient of each of the four explanatory variables measures the partial elasticity of the dependent variable GDP with respect to that variable. As such, each of the partial regression coefficient β1, β2, β3 and β4 are the partial elasticities of GDP with respect to variables INV, TRP, CPI and EXP respectively.

4.4 Explanation of Variables

4.4.1Gross Domestic Product (GDP)

Gross Domestic Product is used to assess the market value of all final goods and services produced during a given period of time within an economy. It also measures the total income of an economy and as such, it is often correlated with standard of living. GDP is used as a reference variable in order to assess the impact of tourism on economic growth in Mauritius. GDP is an important factor used to analyse the development of the tourism sector. As such, in case the tourism sector brings huge foreign earnings, there will be an increase in GDP, suggesting that the economy is flourishing. The GDP figures that are used for the regression have been adjusted for inflation using the GDP deflator.

4.4.2 Investment (INV)

Investment, which is a major component of the gross domestic product of an economy, refers to the acquisition of new capital goods. A positive change in investment may lead to a positive change in income and output of an economy in the short run. Higher level of investment may contribute to aggregate demand while higher level of income may indirectly impact on consumer demand. Investment, which is an injection in the circular flow of income, is a useful tool to analyse the impact of tourism on the economy of Mauritius.

Investment is expected to have the same impact on economic growth as propounded by empirical literature, such as Sargent and James (1997) who found a positive impact of physical capital and investment on growth in Canada over the period from 1947 to 1995.

4.4.3 Tourism Receipts (TRP)

Tourism receipt is a major indicator of the contribution of the tourism sector to the local economy. Tourism receipt represents an inflow of foreign currency in the economy. Such receipts account for a major contribution to the gross domestic product of the Mauritian economy. As such, an increase in tourism earning is expected to have a positive impact on GDP.

Most governments in developing countries encourage international tourism because such tourists bring capital to the country. Earnings of currencies permit governments to finance, at least in part, their development efforts.

Tourism receipt is expected to impact positively on economic growth as postulated by Balaguer and Cantavella-Jorda (2002) or Dritsakis (2004) who claimed that economic growth and tourism are interrelated and established tourism as a driver of economic growth.

4.4.4 Inflation (CPI)

Inflation is defined in economics as a rise in the general level of prices of goods and services in an economy over a period of time. As such, it is a sustained increase in the price level and it may be the consequence either of constant falls in aggregate supply or recurring increases in aggregate demand. As a result, inflation erodes the purchasing power of money, that is, there is a loss of real value in the internal medium of exchange and unit of account in the economy.

An important measure of price inflation is the inflation rate, which can be calculated by taking the annualised percentage change in a general price index over time. This is referred to as the Consumer Price Index (CPI). In Mauritius, the Consumer Price Index is measured by computing the average change over time in the cost of a fixed basket of consumer goods and services. It represents changes over time in the general level of prices of goods and services acquired by Mauritian consumers. Inflation is then calculated by comparing the average level of prices during a 12-month period with the average level during the preceding 12-month period.

One of the most fundamental objectives of macroeconomic policies of many countries, whether industrialised or developing, is to sustain high economic growth together with low inflation. Inflation can bring about uncertainty about the future profitability of investment projects particularly when high inflation is also linked with increased price variability. This would in turn generate more conservative investment strategies, which would ultimately result in lower levels of investment and economic growth.

Inflation is expected to have a negative effect on growth as claimed by Barro (1995) who explored the inflation–economic growth relationship using a large sample covering more than 100 countries from 1960 to 1990.

4.4.5 Exports (EXP)

Export entails the sale of goods and services produced in one country to other countries. There are two types of exporting: direct and indirect. For national accounts statistics, exports consist of transactions in goods and services from residents to non-residents. As such, an export of a good represents a change of ownership from a resident to a non-resident; this does not necessarily imply that the good in question physically crosses the frontier; while an export of services consists of all services rendered by residents to non-residents.

The relationship between export growth, foreign direct investment and economic growth in both developed and developing countries is a question that continues to be of considerable interest. Cross-country trade and capital flows and interpreting the significance of these activities towards economic growth lie at the heart of the debate on economic development policy since the early literature on export and economic growth.

Export is expected to impact positively on growth as postulated by Feder (1982), who mentioned that exports contribute to economic growth in a variety of ways: economies of scale and incentives for technological improvement. Thus, marginal factor productivities are expected to be higher in export industries than in non-export industries.

4.5 Data Sources

For the purpose of this study, time series data has been used. A time series is an ordered chain of values of a variable at equally spaced time intervals. Time series analysis is used for economic and sales forecasting, budgetary analysis, inventory studies or stock market analysis. It encompasses techniques to investigate data in order to extract meaningful statistics and other characteristics of the data.

A time series model indicates that observations close together in time will be more closely correlated than observations further apart. As such, time series models use the natural one-way ordering of time so that values for a given period can be expressed as deriving in some way from past values.

Data has been collected for the period 1976 to 2009. Figures for the explanatory variables namely investment and exports and that for the dependent variable real gross domestic product were obtained from the Central Statistical Office. Data for inflation and tourism receipts was obtained from annual reports of the Bank of Mauritius.

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4.6 Software

The analysis of data will be done using the Microfit 4.0 software. Before carrying out the regression, the stationarity of the variable should be tested in order to avoid spurious results and invalidity of the model. The ARDL model will be evaluated. Furthermore, a co-integration test shall be performed to determine if an Error Correction Model (ECM) must be used.


In this section, the log-linear model specified in the previous chapter is tested for stationarity to ensure that the model does not lead to spurious results. Furthermore, the model is tested for auto-correlation and co-integration using the Durbin-Watson test and Bound test respectively. The model is then regressed using the Microfit software. Finally, results and findings are projected and analysed.

5.1 Test for Stationarity

It is critical to check for stationarity as regression with non-stationary data may lead to spurious result. It was Granger and Newbold (1974) who first used the term “spurious regression” to describe regression results, involving time series, that look good (the t-values suggest that there is a significant relationship between the two variables) when in fact the truth is that there can be no significant relationship between the two variables.

A time series is said to be stationary if its mean and variance are constant over time and the value of the covariance between the periods depends only on the distance or lag between the time periods and not the actual time at which the covariance is computed. The most popular and best known test for stationarity is the Augmented Dickey-Fuller test. The following hypothesis then follows:

H0: δ = 0 i.e. the variable has a unit root.

H1: δ ≠ 0 i.e. the variable is stationary.

To test for stationarity for each variable, the ADF test with 5 lagged differences is used. The results obtained are summarised in the table below.


Variable Description

Test Statistic

10% Critical Value

P-Value MacKinnon

Integration Order


Real GDP
per capita












Tourism Receipts
per capita












1st difference

















The p-value for real GDP per capita is less than 0.1. As such, H0 is rejected and this means that no unit root is present. Therefore real GDP per capita is stationary without differencing it showing that it integrated of order zero, I(0).

This result can be contrasted with a study conducted for 27 OECD countries during the period 1950 to 2004. Ozturk and Kalyoncu (2007), using ADF unit root test on single time series, found that real GDP per capita series of most OECD countries have unit root. This result, however, might be due to the generally low power of this test. Nevertheless, other studies have shown that real GDP per capita tends to be stationary. Ben-David and Papel (1998) have empirical proved that for 16 developing countries the real GDP per capita series are stationary in levels, Aguirre and Ferreira (2001) empirically showed real GDP per capita in the Brazilian economy to be stationary, and Narayan (2008) found the real GDP per capita series for 15 Asian countries to be panel stationary for the period 1950-2002. A more recent study conducted by Murthy and Anoruo (2009) showed that real GDP per capita series, for a panel of 27 African countries from 1960-2005, are stationary with multiple structural breaks taking place in different countries at different dates.

The p-value for investment is 0.0049, which is less than 0.1, H0 is rejected. There is no presence of unit root. Investment is also stationary without being differenced. The variable is therefore integrated of order zero, I(0). Similar result was obtained by Piotr Misztal (2010), who studied investments as a factor for economic growth in Romania for the period 2000 to 2009. Making use of ADF test, the author found that gross fixed capital formation is integrated of order zero, meaning that it is stationary at level form.

However other empirical studies have shown that investment tends to be non-stationary and its first difference tend to be stationary. An empirical investigation carried out by Dritsakis, Varelas and Adamopoulos (2006) concerning the main determinants of economic growth for Greece over the period 1960-2002 showed that gross fixed capital formation used as a proxy for investment is integrated of order one, that is, investment is stationary at first difference; while another study, carried out by Teixeira and Ribeiro (2001) concerning private-sector investment in Brazil during the period 1956-1996, showed that private investment is integrated of order one I(1), being non-stationary in level form while its first difference is stationary.

Concerning tourism receipts, H0 is rejected as in this case the p-value obtained is 0.0029, which is less than 0.1. This confirms the absence of a unit root. Hence this variable is integrated of order zero, I(0).

This result may be contrasted with many studies which have shown that tourism receipts tend to be stationary only at first difference. Norsiah Kadir and Kamaruzaman Jusoff (2010) examined the relationship between tourism and trade that might have evolved in the development of Malaysian economy over the period of 1995:1 through 2006:4. The results of the unit root tests indicate that the data for tourism earnings is stationary in first-difference and not at level form.

Samina Khalil (2007) investigated the role of tourism in economic growth for the Pakistan economy. The author used annual data for the period 1960 to 2005. Using ADF and Philips Perron tests, it was found that the series for tourism receipts is not stationary in its level form, but stationary at the first difference. Mahmut Zortuk (2009) analysed the economic impact of tourism on Turkey’s economy, since tourism in Turkey has emerged as an important sector of the economy generating approximately US$20 billion annually. Data covering the period 1990Q1 to 2008Q3 periods was used in the study. The ADF test proved the existence of unit root, and therefore non-stationarity at level form. However, the first difference of tourism earnings was stationary. Hence it was concluded that tourism earnings for Turkey was integrated of order one, I(1).

The ADF performed on inflation generates a p-value of 0.7409. Thus H0 is not rejected as the p-value is much larger than the accepted threshold of 0.1. A unit root is very likely to be present in the data. As such, the data should be differenced and ADF test should be applied on it. A p-value of 0.0015 is obtained when the test is performed on the first difference of inflation. Thus, H0 is rejected. No unit root is present in the data. Inflation is therefore integrated of order one, I(1).

The result obtained is confirmed by the study of Banerjee and Russell (2006) which found that inflation rate in United States is non-stationary and have a trend term when a hybrid Phillips curve was analysed but when inflation was differenced, the data became stationary.

However, other studies have proved that inflation is stationary at level form. Ericsson, Hendry and Prestwich (1998) found that UK inflation appears to be I(0) rather than I(1). Juan Carlos Cuestas, Barry Harrison (2008) examined the inflation dynamics in a panel of Central and Eastern European countries, which were selected because of their increasing importance in the EU and their likely increased future importance in monetary policy decisions inside the euro area. Making use of unit root testing the authors showed that inflation rates in more than half of the countries investigated are stationary processes.

Since the p-value obtained for exports is 0.0323, which is less than 0.1, H0 is rejected. There is no presence of unit root. The series for export are stationary without being differenced. The variable is therefore integrated of order zero, I(0). However, empirical literature has shown that exports normally tend to be stationary only after being differenced once.

Sharma and Dhakal (1994) concluded that the income and export series for India are non stationary using the Phillips Perron test. Raju and Kurien (2005) used stationarity, cointegration, and Granger causality tests to analyze the relationship between exports and economic growth in India over the pre-liberalisation period 1960-92.The DF and ADF test results for exports showed that the variable is non-stationary at level form but stationary in first difference. Another study was conducted by Chimobi (2010) concerning export, domestic demand and economic growth in Nigeria for the period 1970 to 2005. Using the ADF and Philips Perron test, it was found that the variable for exports became stationary at only first difference

The p-value obtained for the residuals is 0.0720 and thus H0 is rejected. The residuals are stationary as there is no unit root present. The residuals are therefore integrated of order zero, I(0). According to Granger (1986), the residuals should be I(0) in order to avoid the problem of spurious regression in time series.

All the variables are integrated of order zero, I(0) except for inflation which is integrated of order one, I(1). Thus Engle-Granger co-integration method will not work with the data and as such, an autoregressive distributed lag (ARDL) model will be estimated to see if there is co-integration among the variables. The bound test will first be applied to the data to see if our variables are co-integrated. Then the short and long run dynamics will be estimated. The short run dynamics will be an error correction model (ECM) that will give an idea by how much the short run dynamics is joining the long run dynamics. The CUSUM and CUSUMQ will also be deduced.

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5.2 ARDL Model



Variable Description






Real GDP
per capita












Tourism Receipts
per capita






Tourism Receipts
per capita


















R-Bar Squared


DW Statistic


Bound Test

90 % Lower Bound

90 % Upper Bound





An ARDL model is used to find if there is co-integration among the variables. In order to estimate the lag length of the ARDL model, Schwarz Bayesian Criterion (SBC) is used. The latter is minimised when an ARDL (1,0,1,0,0) model is chosen. The model has taken one additional lag from real GDP per capita and tourism receipts per capita into consideration. Since the magnitude of t-ratio for two independent variables, namely investment and tourism receipts is greater than 2 and their p-values are less than 0.05, this means that these two variables are significant. Moreover the t-ratio for exports, which is slightly less than 2, indicates that this variable is slightly significant. However the p-value for inflation indicates that the variable is insignificant.

The model shows a rather high goodness of fit. This is represented by the R Squared figure, which means that all the explanatory variables altogether describe for 99.70 % of the ARDL model. The value of 0.9663 for R-Bar Squared, means that after adjusting for degrees of freedom, all the independent variables together account for 96.63% of the variation in the dependent variable. The Durbin-Watson statistic is around 2, which means that there is no autocorrelation in the residuals. A bound test is performed on the model to see if there is presence of co-integration. Since the F-statistics for the bound test is greater than the 90% upper bound value, the null hypothesis that there is no co-integration is rejected. Thus at 10% level of significance it can be said that variables are co-integrated.

The lagged value for real GDP per capita means that the actual economic growth is affected by the previous year’s growth. As such, if the previous year’s growth increases by 1%, this will entail an increase of 72.45% in the actual real GDP per capita. This can be explained by the fact that the overall contribution of a sector to economic growth is the result of the sector’s own growth rate together with its share in the economy in the previous year.

Real GDP per capita has been constantly increasing from 1980s onwards mainly because of the huge contribution of the Export Processing Zone (EPZ) to the economy of Mauritius. During the period 1980-1988, that output of the EPZ grew rapidly and the EPZ was the main engine of growth for the Mauritian economy. The other sectors, particularly the services sector, contributed more to economic growth of Mauritius as from 1990. This was mainly due to progression of the tourism industry with improved international transportation facilities. The overall contribution of the services sector, comprising of tourism, financial intermediation, trading and real estate has been increasing from the mid 1990s, with a contribution of 40% in 1995 to more than 50% in 2008. However this period was also marked by the decline contribution of the manufacturing and agricultural industry to growth of the economy. This was mainly due to the expiry of the Multifibre Agreement and the Sugar Protocol which provided preferential access to Mauritian products. There was a remarkable progression of financial intermediation and construction from 2005, mainly due to increase offshore business activities and the Integrated Resort Scheme (IRS).

The coefficient for investment is 0.2023 which indicates that if investment increases by 1%, real GDP per capita will increase by 20.23%. This shows that the relationship between the two variables is significant and positive. This is in line with empirical evidences which suggest a positive relationship between the two variables. Many studies have emphasised the diversified role of private and public investments on growth. The public investments in infrastructure are shown to be complementary to the private investments, which in turn increase the marginal product of the private capital, thereby augmenting the growth rate of a domestic economy.

Pineda and Rodriguez (2006) indicated that public investment in infrastructure in Venezuela resulted in higher levels of productivity, thereby generating higher level of growth. De Long and Summers (1991) studied the relationship between machinery and equipment investment, long term economic growth and productivity to see if there were positive spillovers from machinery and equipment investment. They found that the return to society of such investment is large and exceeds the private return and that increasing such investment share by one percentage point could increase long-run growth by 0.2 to 0.3 percentage points.

For Mauritius the positive relationship can be explained by the fact that government spending can boost economic growth by putting money in the hands of the public. As such, public investment may lead to an increase in employment which should multiply throughout the economy. Public investment in infrastructure development may foster further investment by the private sector. However, public investment may also crowd-out private investment which can have negative implications for growth.

The coefficient for tourism receipts per capita is 0.7659 which indicates that if tourism receipts increases by 1 %, real GDP per capita will increase by 76.59 %. The relationship between the two variables is implicitly suggested to be positive. This is in line with the empirical evidence which suggests a positive relationship between tourism contribution and economic growth. Dritsakis (2004) showed that tourism has a long-run economic growth effect on Greece. He found a bi-directional causality between tourism and economic growth and that there was the existence of a co-integrating relationship among the three variables used. The elasticity of tourism expenditure was 0.31 for Greece. Similarly Balaguer and Cantavella-Jorda (2002) confirmed the tourism-led growth hypothesis for long-run economic performance of Spain. They found a co-integrating relationship indicating that tourism positively affects economic growth over time and that the corresponding elasticity of tourism expenditure, equivalent to 0.30, has a significant effect on economic growth. Past tourism receipts also seem to have an effect on growth; an increase of 1% in tourism receipts will increase growth by 63.48% in the following year. This means that tourism earning not only affects the economy today but also spreads its effect in the following years.

For inflation, the coefficient of -0.0481 suggests that the relationship between the inflation and real GDP per capita is negative. As such, a 1% increase in inflation is likely to result in a 4.81% decrease in economic growth. Inflation may bring uncertainty about the future success of investment projects particularly when high inflation is linked with increased price variability. This entails more conservative investment strategies, ultimately leading to lower levels of investment and economic growth.

Empirical literature also suggests a negative relationship between the two variables; Barro (1995) assessed the effect of inflation on economic growth using data for 100 countries from 1960 to 1990. Barro incorporated the inflation rate over each period as an explanatory variable together with the other growth determinants. He found that inflation had a negative effect on growth, with a coefficient of –0.024. Ghosh and Phillips (1998) examined the relationship between inflation and growth using data set on real per capita GDP growth, and period average consumer price inflation, corresponding to 145 countries for the 1960 to 1996. They proved that at very low rates of inflation, inflation and growth are positively correlated. Otherwise, inflation and growth are negatively correlated.

The value of 0.0972 for exports implicitly suggests a positive correlation between the variable and real GDP per capita, meaning that a 1% increase in exports will yield a 9.18% increase in economic growth. Ricardo (1817) mentioned that trade, particularly exports, facilitates products output with a comparative advantage in a country resulting to a higher level of national wealth.

Michealy (1977), using cross-section data of 41 less developed countries, found the evidence of a positive relationship between export growth and economic growth while highlighting the fact that export expansion impacts on economic growth only when countries achieve some minimum level of development. Tyler (1981) using a sample of 55 middle income developing countries found evidence for a strong positive association between export growth and economic growth. Rana (1985) estimated an export-augmented production function for 14 Asian developing countries including Bangladesh, India, Nepal, Pakistan, and Sri Lanka. The results showed that exports contribute positively to economic growth.

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5.3 Short Run Dynamics

The short run dynamics can be represented by the following equation

ΔY t = Φ0 + φ1ΔINVt + φ2ΔTRP t + φ3ΔCPI t + φ4ΔEXP t + σecm t-1

The short-run coefficients obtained are listed in the table below































The ecm value can be obtained from the equation below

ecm = LNGDP - .73443*LNINV - .47608*LNTRP + .17460*LNCPI - .35277*LNEXP

When two variables are co-integrated, this means that there is a stable long-run relationship between them. However, in the short-run there may be disequilibrium and this may be corrected by error correction model (ECM), which is a balancing point where the short-run model and the long-run model meet.

The coefficients of the first difference of change in investment, tourism receipts, inflation rate and exports of the short-run model are exactly the same as the coefficients of the ARDL model. The coefficient of ecmt-1, σ, is negative and significant since it is greater than 2 and the p-value is less than 0.05. This indicates that the error correction model is valid and confirms the presence of co-integration in the long run. The coefficient size, 0.2755 refers to the speed at which real GDP per capita adjusts to any discrepancy between investment, tourism receipts, inflation and exports. Nearly 27.5 percent of the disequilibria in real GDP per capita of the previous year’s shock adjust back to the long-run equilibrium.

5.4 Long Run Dynamics

The long run coefficients obtained are summarised in the following table


























The coefficient of investment for the long-run is greater than that for the short-run, due to the fact that the impact on growth in long term is more consequent. A rise by 1% in investment will increase real GDP per capita by 73.44%. This is in line with the study carried out by Chimobi (2010) to estimate the impact of investments and export on long run economic growth of Nigeria for the period 1970-2005. He found that that increase in investment will lead to production of more good which will cause growth in the economy on one hand; and on the other hand, economic growth will guarantee increase in Investment. This rise in investment will generate development projects such as electricity supply, good road network, good medical care and host of other projects being carried out in Nigerian economy and as such per capita income will increase.

An increase of 1% in tourism receipts will increase economic growth by 47.61% in the long-run. The variable is significant as its p-value is less than 0.05 and the t-ratio is greater than 2. Tourism receipts has a positive long-run relationship with growth as claimed by Balaguer and Cantavella-Jorda (2000) for Spain, whereby they found that long-run economic growth is sensitive to persistent expansion in international tourism. The increase in tourism activity produced multiplier effects over time. Dritsakis (2004) in a study on Greece’s long-run economic growth showed that international tourism earnings have a strong positive causal relationship with economic growth in the long-run.

The coefficient of inflation indicates that the latter has a higher negative impact on economic growth in the long-run than in the short-run, as an increase of 1% in inflation will lead to a fall of 17.46% in real GDP per capita. Bruno and Easterly (1995), using data series of 26 countries that experienced inflation crises at some point in time over the 1961-1992 period, found a negative relationship between inflation and growth. They claimed that inflation might alter the long-run average growth rates. Barro (1995), using data for about 100 countries for the period 1960 to 1990, found that an increase in average inflation of ten percentage points per year lowers the growth rate of per capita GDP by 0.2-0.3 percentage points per year.

If exports increases by 1%, this will yield a 35.28% increase in real GDP per capita; the impact of exports on economic growth is more significant in the long-run than in the short-run. This may be due to trade liberalisation and removal of price controls, which enabled the textile sector to develop, whereby Mauritian products were able to differentiate themselves from the low cost products of China. Kaushik (2008) investigated the relationship between economic growth and export in India during the period 1971- 2005, found that there exists a long-run relationship between real exports and real GDP. As such, a 1% increase in exports raises GDP by an estimated 0.42% in the long run.

5.5 Test for Stability

To ascertain the goodness of fit of the ARDL model, the stability test is conducted using the cumulative sum of recursive residuals (CUSUM) and the cumulative sum of squares of recursive residuals (CUSUMQ), to know whether there has been any sort of structural change during the period 1976-2009.

The stability tests from the plot of cumulative sum and cumulative sum of squares of recursive residuals show that the model is stable, as both graphs lie within their respective 5 percent significance level bands.


6.1 Conclusion

Over the last decades, Mauritius has achieved considerable economic success and tourism has played a crucial role in this success, especially in terms of foreign exchange and employment creation. Given the importance of this industry, the aim of this dissertation was to evaluate the impact of tourism on economic growth in Mauritius. A log-linear model was estimated, and it includes variables such as tourism receipts, investment, inflation and exports, while real GDP per capita is used as the dependent variable to quantify the impact of tourism on growth.

The results showed a positive and significant relationship between tourism earnings and growth rate. Among all the independent variables, it is tourism receipt which has the most significant impact on gross domestic product. Also the R-Squared value shows that the model has a high goodness of fit. Therefore, it can be concluded Mauritius benefits a lot from tourism, particularly in terms of foreign exchange earnings and employment since the industry is mainly labour-intensive.

With the declining effectiveness of both the agricultural and textile sectors, in terms of the respective contribution to GDP, the Government has to capitalise on the tourism industry to maintain and strengthen economic growth of the country. The tourism industry has emerged as one of the fastest growing productive sectors in Mauritius. The Government has to sustain the image of high quality destination and has to preserve the environmental integrity of the island.

The contribution of tourism to growth depends on the extent to which foreign earnings are retained in the economy. It is normally believed that the degree of leakage for the industry is low since the majority of hotels have been constructed using local capital. Although the Government aims to attract foreign investors for the development of the tourism sector, such investors are required to enter in a joint-venture with local partners. To further reinforce the industry, the Government accords numerous fiscal and other incentives to investors.

6.2 Recommendation

Tourism is seen to be a major contributor of economic growth in Mauritius and as such, the Government needs to capitalise on this industry for the economy to progress further. With the aim to attract more than two million tourists annually by 2015, it must exploit the award received for “World Leading Island Destination” and must develop a strategy to boost investment in this sector and such action must over a long-term investment to sustain a constant yearly growth since competition is quite fierce in this particular market segment.

The financial mess of the euro-zone countries has affected purchasing power in such countries. Since the tourism industry is highly dependent on that zone, hotels must strive to reduce the charges, particularly during the off-peak season in order to counteract this problem. With the emergence of other tourist destinations such as Maldives, Bali, Singapore and Thailand, the local uthorities must engage in more promotional and marketing campaigns in non-traditional tourism markets.

Other policy recommendations for the tourism industry are:

Tourism is without doubt an important sector for the Mauritian economy and if proper policy measures are implemented to further its development, the country will be able to reap more foreign exchange earnings and consequently more jobs will be created. As such, this will improve economic growth for the country.

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