Tourism and income inequality in Mauritius

An empirical investigation

Authored by: Sheereen Fauzel

The Routledge Handbook of Tourism Impacts

Print publication date:  May  2019
Online publication date:  April  2019

Print ISBN: 9781138494961
eBook ISBN: 9781351025102
Adobe ISBN:

10.4324/9781351025102-9

 

Abstract

Using a dynamic vector error correction model catering for dynamic, endogeneity, and causality issues, this study investigates the link between tourism development and income inequality in Mauritius using time series data for the period 1983–2016. The results show that tourism expansion has contributed towards reducing inequality in both the short run and long run. Furthermore, the results also confirm the presence of uni-causality in the tourism-inequality model. Also, inflation and unemployment are seen to increase income inequality in the long run whereas human capital reduces income inequality. The short-run results confirm the economic-driven growth hypothesis for the case of Mauritius.

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Tourism and income inequality in Mauritius

Introduction

Mauritius is a tropical island and is renowned as a popular destination for tourists from all over the world looking for a high-end holiday. It has a wide range of natural attractions, with a subtropical climate, beautiful, clear beaches, and tropical fauna and flora complemented by a multi-ethnic, multicultural population that is friendly and welcoming. Moreover, Mauritius has high-class beach resorts and hotels. The hotel industry has constantly upgraded the quality of its service to fulfil the growing international demand from tourists. This industry has experienced massive growth over recent years. The island had around 18,000 visitors in 1970, and, in 2017, the number of visitors was approximately 1,300,000. The tourism sector is considered a main pillar of the Mauritian economy and has contributed massively towards economic growth. The industry generates around 40,000 direct employment jobs. 1 It has considerable advantages for the economy in terms of creating direct and indirect employment. As such, it is expected to contribute towards a reduction in income inequality in the country. Referring to the Kuznets curve hypothesis, and linking tourism development to economic development, as tourism expands it is considered to increase inequality and then reduce inequality with time as there is more development.

Referring to the literature, there is, to date, no study which has assessed the impact of tourism development on income inequality in Mauritius. As such, there is a need to analyse the implications of the dynamics of tourism expansion for the economy. To that end, although it is by and large acknowledged that there are benefits to be gained from tourism, unfortunately, however, it is also true that firms do pose certain problems in certain cases.

Given the above, the focus of this chapter is an attempt to fill such a gap and it aims to add to the existing literature by investigating the direct and indirect relationship between tourism development and income inequality in Mauritius. In this regard, this study uses a rigorous dynamic time series analysis, namely a dynamic vector error correction model (VECM), to carry out the proposed investigation. Such a procedure ensures that the dynamic behaviour of the time series under consideration is properly captured, while simultaneously catering for endogeneity and causality issues. Any feedback and indirect effects which might be present will also be detected within the VECM. The model also simultaneously allows the identification of any bidirectional and/or unidirectional causality between the variables of interest.

The rest of this chapter is organized as follows: the second section discusses the theoretical and empirical literature; the third section provides a brief overview of the evolution of the tourism sector and inequality in Mauritius; the fourth section defines the methodological approach used; the fifth discusses the findings from the study; and, in the final section, some conclusions are presented.

Literature review

The tourism sector is regarded as an important sector having important effects on the economy of a country. Many scholars have investigated the impact of tourism development on the economic growth of a country. For instance, the tourism-led hypothesis has been overwhelmingly discussed in various studies. This theory states that international tourism leads to a significant increase in economic growth. Papers such as those of Sinclair and Stabler (2002) and Samimi, Sadeghi, and Sadeghi (2011) prove this relationship in their studies. Apart from the creation of growth, tourism development has various spill-over effects on an economy. A boost in the tourism sector can help an economy to have structural diversification as well. For instance, we have the structural bonus hypothesis. This hypothesis states that, during industrial development, factor inputs shift to more productive branches (Timmer and Szirmai, 2000). Hence, structural change prompted by tourism development has the potential to promote productivity and economic growth. For instance, Fauzel, Seetanah, and Sannassee (2017) show that tourism development has positively influenced economic growth in Mauritius. In fact, they found that a 1% increase in tourist development contributed to a 0.45% increase in the economic growth of Mauritius. Similar results were obtained by Dritsakis (2004), Kim, Chen, and Jang (2006), and Eugenio-Martín, Morales, and Scarpa (2004). Indeed the tourism industry in Mauritius has recorded a consistently robust performance since 1995. Mauritius has also registered an impressive inflow of tourism receipts.

Tourism development can further spill over to employment in the country. Tourism can promote direct employment, indirect employment, and induced employment. For instance, the tourism industry employs local citizens in hotels, restaurants, and entertainment and tourist services which cater directly for tourists or through the multiplier effect (Haley and Haley, 1997). Furthermore, in view of the prevalence of service quality in the tourism sector, there is a constant demand for training which can only serve to upgrade the skills of local employees working in the industry. And in this regard, skill transfers are common practice for international hotels.

Klytchnikova and Dorosh (2009) argue in their paper that tourism revenues extend beyond hotel operators and employees, tour operators, restaurateurs, and shop workers who sell goods and services to tourists. Expenditure by tourists at least in part extends to local goods and services, which further raises output and incomes. The multiplier effect can thus be huge. The net impact of tourism on income generation and distribution depends on more than just the direct spending by tourists on various commodities and services. Likewise, poverty reduction impacts go beyond the employment and income generated by direct contacts with tourists as a function of multiplier effects of other sectors on output. Hence, the ultimate distribution of incremental revenues from increased production to household groups (poor and non-poor) also varies with several additional factors (labour and capital). This paper found that tourism expansion has benefitted both the economy and the poor in Panama. Pant (2011) investigated tourism’s impact on income inequality using cross-country and panel data regressions. In his investigation, he found that the tourism sector has decreased gross income inequality in the sample of countries used in his study.

However, there are conflicting views on whether tourism reduces income inequality or not. For instance, it has been found that tourism expansion in a country with surplus tourist attractions can reduce income inequality. On the other hand, several scholars have found that tourism expansion can increase inequality. For instance, Alam and Paramati (2016) investigated the impact of tourism on income inequality in developing economies. Their investigation utilizes a balanced panel data set from 1991 to 2012 on 49 developing economies around the world. The study found that there is a long-run equilibrium relationship among the variables. Results from long-run elasticities indicate that tourism increases income inequality significantly. Further, the long-run elasticities on squared tourism revenue confirm the existence of the Kuznets curve hypothesis between tourism revenue and income inequalities, meaning that, if the current level of tourism doubles, then it will significantly reduce the income inequality in developing economies.

Similar findings were found by Raza and Shah (2017), who examined the relationship between tourism and income inequality in the top 43 tourist arrival countries by using the data over the period of 1995–2015. The investigation applied advanced econometric techniques which include cross-sectional augmented IPS (CIPS) unit root test, bootstrap co-integration, Pedroni co-integration, fully modified ordinary least squares, and a heterogeneous panel causality technique. They found that that all the variables are co-integrated in the long run. That is, tourism has a positive effect on income inequality overall and in the regional sample. Furthermore, the Kuznets curve hypothesis was also tested and found to exist. This concludes that, if the examined countries increase their tourism revenue, this will help them to reduce income inequality.

Another strand of literature shows that inequality in various regions is increased owing to international tourism development. This was found in the studies by Göymen (2000) and Seckelmann (2002) for the case of Turkey as developed and coastal locations receive more tourism-related investments and superior policies. Hence, given such a situation, these regions have grown much faster, and therefore regional inequality is further enlarged. On the other hand, Krakover (2004) compared the centre and peripheries in Israel and noted that Israel’s tourism success in reaching balanced regional economic development is due to special situations, namely, the size of the country, government policies, and security issues. Based on a conditional convergence model, Proença and Soukiazis (2008) observed that international tourism has a noticeable influence on decreasing regional gaps among different locations in Spain, Italy, Greece, and Portugal. Also, Soukiazis and Proença (2008) show that tourism increases the convergence rate within Portugal’s NUTS-2 and NUTS-3 regions.

Moreover, when domestic tourism is greater than international tourism both in terms of economic contribution and size, then domestic tourism has the capacity to reduce disparities in less-developed countries (Massidda & Etzo, 2012). In relation to this argument, Seckelmann (2002) argued that south-eastern Turkey and other less-developed regions with more natural and historical resources attract more domestic tourists, which is considered to be an instrument to achieve balanced regional development. Also, Haddad, Porsse, and Rabahy (2013) applied an input–output model to empirically study the regional effect of domestic tourism and found that domestic tourism narrows regional disparity in Brazil.

Li, Chen, Li, and Goh (2016) examined the role of tourism development in reducing regional income inequality in China. The study proposed a spatiotemporal autoregressive model to capture spatial and temporal dependence as well as spatial heterogeneity. They included tourism development as a conditional convergence factor in order to examine whether the convergence speed was accelerated by regional tourism development. They also tested the effects of international and domestic tourism in narrowing regional inequality, both globally and locally. The empirical results indicated that tourism development contributes significantly to the reduction of regional inequality, with domestic tourism making a greater contribution than international tourism.

Income inequality can be affected by other variables as well. For instance, the paper by Bulíř (2001) contributed to the income inequality literature that is based on the traditional Kuznets model. He found that development, state employment, fiscal redistribution, and price stability improve income inequality in a given country. The positive impact of price stability on income distribution is found to be nonlinear. The reduction in inflation from hyperinflationary levels significantly lowers income inequality, and further reduction towards a very low level of inflation seems to bring about negligible additional gains in the Gini coefficient.

Also, inequality can be affected by GDP and vice versa. Hence, it can be said that there is a causal link between GDP and income inequality. Such a finding is found by Brueckner and Lederman (2017), whereby the initial distribution of wealth affects aggregate level of output and investment in the short run and long run.

Analysing the literature, it can be observed that there is mixed evidence on the relationship between tourism development and income inequality. Moreover, it is as clearly perceived that economic growth, inflation, and unemployment all have a significant impact on income inequality.

Overview

Mauritius is a small multicultural island state that has made a great effort to foster equal opportunity for all. The economy, which was a monocrop one based on the sugar sector, has now been transformed into a well-diversified economy. The first phase of economic transformation occurred with the boom of the EPZ sector in the 1980s. This transformation generated lots of employment and growth in the Mauritian economy. This was followed by development in the tourism sector.

The island’s clear postcard beaches, calm sea conditions, tropical fauna and flora, complemented by a multi-ethnic, multicultural population that is friendly and welcoming, have contributed to massive tourism development in the country. These tourism assets are Mauritius’s main strengths, especially as they are backed up by top-class beach resorts and hotels and reliable and operational services and infrastructures. The hotel industry in Mauritius is a very well-organized industry. The industry has constantly upgraded the quality of accommodation to cater to the demands of the international traveller. Many resorts and hotels have been equipped with the latest technology and services for the indulgence of tourists, with a large variety of services such as saunas, massages, private hot tubs, and well-designed gardens, providing a fairylike atmosphere (see the Mauritius Attractions website). 2

This sector has contributed a lot towards the economic growth of the country. Tourist arrivals in 2017 reached around 1,341,860, and tourism receipts were about 60.3 billion Mauritian rupees. Tourist arrival in Mauritius has consistently grown in recent years, and, following the government efforts to develop the local tourism sector, it is most likely therefore that the tourism sector will continue growing in coming years. Also, the government has been putting much effort into developing the tourism sector by setting clear policies, eliminating bureaucratic procedures, offering incentives, and creating an environment conducive to investment. Figure 8.1 shows the evolution of tourist arrivals in Mauritius, and the growth can clearly be observed.

Evolution of tourist arrivals in Mauritius

Figure 8.1   Evolution of tourist arrivals in Mauritius

Source: Author computation.

However, regarding income inequality and poverty in the country, it can be observed that some proportion of the population is still left out. The Mauritians of African origin are disproportionately present within that group. We can still see jobless growth, growing inequality, and inequalization in the country. The main pillars of the economy remain the tourism and financial sectors; however, the country is experiencing rising unemployment.

It is now struggling to maintain growth rates at reasonable levels, but the rising inequality and poverty, as well as other associated problems, constitute major challenges. Mauritius has growing unemployment, which currently hovers around 7% and is much more concentrated among women. This rapid increase in youth and female unemployment is very serious, mainly in a context of growing inequalization and rising poverty (Bunwaree, 2014). Inequality in Mauritius has been rising. Measured by the Gini coefficient, inequality in Mauritius is now high. Referring to the World Bank’s report “Mauritius – Inclusiveness of growth and shared prosperity”, it says “On inequality, Mauritius also fared well compared to its peer middle-income countries, with a Gini coefficient 0.39 in 2012. On the negative side, Mauritius’ growth has not been equally shared” (Sulla et al., 2015, p. xi).

Figure 8.2 shows the evolution of the Gini coefficient in Mauritius.

Evolution of GINI coefficient in Mauritius

Figure 8.2   Evolution of GINI coefficient in Mauritius

Source: Author computation.

Methodology

Model specifications

The main objective of this study is to investigate the relationship between tourism and income inequality in Mauritius for a period of 34 years (1983–2016). This section describes the model adopted and the empirical indicators of tourism, inequality, and other control variables used in the model. The basic specification of the model is based on the principles of some earlier studies carried out by Pant (2011) and Li et al. (2016). In this regard, the econometric model takes the following functional form:

INQ = f (TOU, RGDP, UNEM, DEF, EDU) (1)

The model is used to analyse the impact of tourism development on income inequality, which is measured by the Gini coefficient in Mauritius. The variable of interest in this study is tourism development and it is measured by tourists’ arrivals. The reason for emphasising tourism is inspired by economic theories. For instance, the Heckscher–Ohlin theorem states that the relative abundance of a country’s factor of production will provide the country with a comparative advantage in the production of the goods that use the relatively abundant factor extensively. As per this theory, tourism is relatively more labour-intensive and, hence, it has a comparative advantage because of the excessive quantity of cheap labour. As per this theory, tourism becomes more predominant because of a great amount of the exclusive properties of a country such as sea, sun, climate, mountains, and so on. Likewise, it also converts untradable goods into tradable because both the production and consumption of tourism take place at the destination. Hence, there is an increase in tourism receipts as well as the creation of employment in the country. It thereby allows the reduction of income inequality. Hence, tourism development has the potential to reduce the income inequality in the country.

Furthermore, the relationship between aggregate output and the distribution of income is an important topic in macroeconomics. Accordingly, economic theory suggests that there is a link between inequality and aggregate output, and that the effects differ between rich and poor countries. Referring to the work by Galor and Zeira (1993), a model is suggested whereby the credit market imperfections and indivisibilities in human capital investment are used to show that inequality affects aggregate output in the short run as well as in the long run. This model forecasts that the effect of inequality differs across countries and time depending on initial wealth. Brueckner and Lederman (2017) suggest that a causal link exists between inequality and GDP, whereby the GDP of the country also affects income inequality. Hence, the variable GDP per capita is included in the model to investigate this link.

In addition, it has been observed that income inequality and human capital are linked. Various studies shows that, in poor countries, income inequality and human capital are significantly positively correlated. In rich countries, the relationship between income inequality and human capital is negative (Brueckner and Lederman, 2017). Hence, the secondary enrolment rate is included to capture the link between income inequality and human capital in Mauritius.

Inflation is seen to affect the cost of living of workers and reduces their purchasing power. In fact, fewer studies have been done on the link between inflation and income inequality. As observed by Hudson, Roth, Madden, and Hudson (2015), as inflation goes up, income inequality decreases, reaches a minimum level, and then starts rising again. The findings of their paper show the existence of the Kuznets hypothesis across the countries. Hence, the GDP deflator is included in the model to investigate the link between inflation and income inequality.

Work income is considered to be very important to households’ economic status. Households that receive no income from work have far lower levels of overall income and expenditure than households that do receive some income from work. The study by Tregenna and Tsela (2012) shows that the rate of unemployment accounts for a significant part of earnings inequality.

The econometric specification for the present study can be written as follows, as derived from Equation 1:

lnINQt = α0 + β1 lnTOUt + β2lnGDPt + β3 lnUNEMt + β4 lnDEFt + β5lnEDUt+ µt  (2)

where t denotes the time dimension, and the natural logarithms of the variables are employed for ease of interpretation (that is, in percentage terms).

Estimation issues

A VAR approach is used to delineate the relationship between tourism development and income inequality. Such an approach does not impose a priori restriction on the dynamic relations among the different variables. It resembles simultaneous equation modeling, whereby several endogenous variables are considered together. Hence, the VECM linking short-term and long-term causality between tourism and inequality is set as follows:

3 Δ lnINQ t = α 0 + j = 1 n α 1 Δ ln TOU t j + j = 1 n α 2 Δ ln GDP t j + j = 1 n α 3 Δ ln UNEM t j + j = 1 n α 4 Δ ln DEF t j + j = 1 n α 5 Δ ln EDU t j + η Ε CT t 1 + ε t

The coefficient of the error correction term (ECTt-1) indicates whether there exists a short run relationship among the time series variables.

Furthermore, applying regression to time series data may generate spurious results (Granger and Newbold, 1974; Phillips, 1986), given the possibility of non-stationarity data. As such, undertaking a check as to the stationarity of data is a prerequisite for applying the co-integration test. As a result, the augmented Dickey–Fuller (ADF) test (Dickey and Fuller, 1979, 1981) and the Elliot–Rothenburg–Stock point optimal were applied.

Analysis of findings

From the application of the ADF (Dickey and Fuller, 1979) and Elliot–Rothenburg–Stock point optimal unit-roots tests, it is observed that all the variables are integrated of order 1 and stationary in the first difference. The Johansen maximum likelihood approach is subsequently used to test the presence of co-integration in a vector error correction model in both specifications. Trace statistics and maximal eigenvalue confirm the presence of co-integration, and thus it is concluded that a long run relationship exists in both the above specifications.

Empirical results

The long-run dynamic estimate of Equation 2 is reported below:

lnINQ = -4.994 - 0.105lnTOU + 0.465lnGDP + 0.034lnUNEM + 0.0008lnDEF -0.127 ln EDU

***  ***  ***  ***  ***  **

** significant at 5%, ***significant at 1%

The long-run equation yields motivating results. As the main research objective of the study is to analyse the impact of tourism development on income inequality growth in Mauritius, an analysis of the results for the variable LTOU is done first. From the results, it is observed that tourism development has contributed towards reducing income inequality in the economy in the long run, as supported by the negative and significant coefficient of the variable. In fact, a 1% increase in tourism development reduces income inequality by 0.11%. This result is in line with Pant (2011), who investigated tourism’s impact on income inequality using cross-country and panel data regressions. His results from the regression analyses show that the tourism sector has decreased gross income inequality in the sample of countries used in his study. Regarding the Mauritian economy, it has undergone a complete transformation since independence. From a monocrop agricultural economy, it has transformed into a well-diversified economy with agro-industry, manufacturing, financial services, tourism, retail trade, and information and communication technology as its main pillars (Three year strategic plan report, Mauritius, 2017). 3 Tourism has contributed towards boosting direct, indirect, and induced employment in both the long run and short run in Mauritius (Fauzel, 2016). This can partly explain the results obtained above. When workers are able to obtain an income, it can significantly reduce income inequality in the country.

Inflation is also included in the model to investigate the impact of increases in general price levels on income inequality. The result shows that an increase in inflation increases income inequality (this supports the results of Bulíř, 2001). This result was predictable, as inflation leads to redistribution of income, and there is a tendency for wealth and income to flow to the rich.

Zooming in on the unemployment results, it can be seen that higher unemployment increases income inequality. Unemployment results in inequality when it continues for succeeding cycles. Unemployment, be it cyclical, structural, or frictional, adds to the despair of the unemployed. Human capital is seen to reduce inequality. The results are as expected and are negative and significant. On the global level, if we consider the case of developing countries, a great deal of effort has been made by these economies to eradicate illiteracy. As a result, the inequality in the distribution of education has been reduced by more than half (Castelló-Climent and Doménech, 2014).

Short-run regression

In the presence of co-integration, we subsequently estimate a VECM including the error correction term, which should allow for an investigation of the dynamic nature of the model. The VECM specification forces the long-run behavior of the endogenous variables to converge towards their co-integrated relationships, which accommodates short-run dynamics. In this study, the VECM is estimated using an optimum lag length of 1. The empirical results of the short-run estimates for Model 1 of the VECM are displayed in Table 8.1.

Table 8.1   Short-run dynamics (dependent variable: TOU)

Error Correction:

D(LINQ)

D(LTOU)

D(LGDP)

D(LUNEM)

D(LDEF)

D(LEDU)

CointEq

-0.17372

0.85414

-0.311766

3.38043

9.72623

-0.68933

***

D(LINQ(-1))

0.97298

-5.99704

-0.26959

1.84678

-53.8367

0.069603

*

D(LTOU(-1))

-0.00852

0.09161

0.05654

-0.31054

-0.96675

-0.05669

***

**

*

D(LGDP(-1))

-0.04019

2.12541

-0.30685

0.83216

25.0088

-0.24755

*

D(LUNEM(-1))

0.00318

0.10193

0.01474

0.18558

1.68012

-0.00024

***

**

*

D(LDEF(-1))

-0.00013

0.00278

-0.00223

0.00635

-0.29880

0.00025

***

***

***

**

***

D(LEDU(-1))

0.08917

-0.39602

-0.08816

0.63464

6.48259

0.37338

**

Constant

0.00142

0.04970

0.049046

-0.02615

-1.24611

0.03378

***

**

**

*

**

Notes: *significant at 10%, ** significant at 5%, ***significant at 1%.

Table 8.1 is a composite table, where each column can be viewed and analysed as an independent function; that is, each column in the table corresponds to an equation in the VECM. The variable named in the first cell of each column is viewed as the dependent variable. The estimated coefficient of the explanatory variables is reported in the cells. Our focus will be on the first column.

Analysing the short-run estimates of Equation 1 – that is, the regression equation with inequality as the dependent variable – it may be argued that, in the short run, tourism development does have a negative effect on income inequality, albeit the coefficient being smaller, which tends to support the argument that such development takes time to have its full effect on income inequality. For instance, in Mauritius, tourism development has increased considerably from 1970 to 2017. There has been a 7,123% increase in tourists’ arrivals. Hence, it can be argued that the results support the Kuznets curve hypothesis. With more tourism development, income inequality has decreased. In this instance, a 1-percentage-point increase in the growth rate of tourism leads to a 0.009-percentage-point decrease in the income inequality after one year. Additionally, but similar to the findings uncovered for the long-run equation, unemployment and inflation are also significant. Regarding the variable GDP, it can be observed that an increase in economic growth leads to a reduction in income inequality. For instance, a 1% increase in GDP has led to a 0.04% decrease in income inequality. This result supports the results of Brueckner and Lederman (2017).

Furthermore, and as discussed previously, the VAR/VECM framework allows us to gauge more interesting insights into endogeneity issues and also allows us to detect any potential indirect effects. Whereas our results show that tourism development influences income inequality, the results reported in Table 8.1 demonstrate that income inequality does not have any effect on tourism development in the country. In this regard, and more specifically referring to the tourism equation depicted in the third column of Table 8.1, it is observed that a reverse causation does not exist between income inequality and tourism development. Thus, the results demonstrate a unidirectional relationship flowing from tourism development to income inequality.

In addition, referring to Column 4 of Table 8.1, the above result confirms the tourism-led growth hypothesis, and, hence, an increase in the growth rates leads to tourism development in the present study in the short run.

Given the above, the overall results tend to provide support to the existence of a negative and significant relationship between tourism development and income inequality, both in the short run and in the long run for the case of Mauritius.

Conclusion

Based on the VECM framework adopted in this study, the main objective is to investigate the relationship that might exist between tourism development and income inequality in Mauritius over the period 1983–2016. Referring to the results, it is found that tourism expansion in the country reduced income inequality in the country, both in the long run and in the short run. In fact, the government has played an important role in developing the tourism sector in Mauritius. Various incentives have been given to investors in the tourism sector to boost investment in this field. For instance, liberalization policies have been adopted by the Mauritian government, and thereby foreign investment was allowed to flow into key tourism elements, such as restaurants, yachts, and travel agencies, among others. These policies have not only attracted more investment in the sector, but have also brought the capital needed for further investment, and also the necessary technological know-how and skills, and they have led to the construction of world-class hotels and villas. Direct and indirect employment has also increased to a large extent. Moreover, inflation and unemployment are seen to increase income inequality in the long run, whereas human capital reduces income inequality. Regarding the short-run results, a unidirectional relationship is observed flowing from tourism development to income inequality. Moreover, the results confirm the tourism-led growth hypothesis in the country.

Referring to the results obtained above, the government should further encourage the tourism sector to expand, given its numerous advantages for the economy. It also contributes towards reducing income inequality. The government has been encouraging the building of new hotels, increasing the number of rooms available on the island. It also came up with a policy to launch numerous integrated resort scheme projects and organize a selection of international cultural events. However, other policies could be adopted to further reduce inequality in the country. For instance, the adoption of the minimum wage in Mauritius could contribute to reducing inequality to a large extent. Policies to further increase access to education can also be successful, as well as the adoption of a more progressive tax system.

Notes

References

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