Chapter

Chapter 9E. Mauritius

Editor(s):
Kalpana Kochhar, Sonali Jain-Chandra, and Monique Newiak
Published Date:
February 2017
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Author(s)
David Cuberes, Monique Newiak and Marc Teignier 

Potential growth in Mauritius could decline in coming decades as a result of a stall in population growth and a rise in dependency ratios (the percentage of the population that is not of working age). However, Mauritius possesses a large pool of educated women who currently do not participate in the labor market. Real GDP in Mauritius has been an estimated 22 to 27 percent lower in the past compared with a situation in which there were no such gender differences in labor force participation and entrepreneurship. Closing these gender gaps over time could mitigate the drop in economic growth resulting from demographic changes. Evidence from microlevel data suggests that awareness of employment programs in Mauritius is positively associated with both female and male labor supply, as are demographic characteristics, education levels, and expected wages. Policies to expand the supply and quality of childcare, extend parental leave to fathers, increase financial literacy, and promote flexible work arrangements can complement programs by the Mauritian government to stimulate female labor supply.1

Demographic Challenges

Mauritius could face a rapid decline in its labor force in coming decades (Figure 9.16). Population growth has already stalled, due in part to a significant decline in fertility below the global replacement rate of 2.3 births per woman. With little migration and continued low fertility, the United Nations Population Division estimates that Mauritius’s population could face a rapid decline in the next decades, with large implications for the potential labor force and significant increases in the dependency ratios.

Figure 9.16.Labor Force Projections for Mauritius, 2015–2100

(Thousands of people, ages 15–64)

With substantial gender gaps in economic participation, Mauritius already loses out on potential growth; closing gender gaps may help address the demographic challenges as well. Gender gaps in education have closed in Mauritius, but the gaps in labor market participation remain high. Women already in the labor market are more likely than men to be unemployed, earn less on average, and are less likely to work as an entrepreneur. A number of studies have highlighted that such gender gaps are associated with worse growth and development outcomes (WEF 2014; Cuberes and Teigner 2016; IMF 2015; Elborgh-Woytek and others 2013; Gonzales and others 2015b). Indeed, during the past decade, GDP per capita in Mauritius has been lower by about one-quarter compared with a situation without gender gaps. Closing these gaps is also a possible solution to meet the demographic challenge, as shown in this analysis based on the calibration of an occupational choice model.

Gender Gaps in Mauritius

The gender gap in economic participation has been decreasing but remains relatively high (Figure 9.17). Female labor force participation has increased relative to males in recent decades and is now in line with that of the average middle-income country. Young women have increasingly joined the labor market, which has driven this trend. In general, labor force participation rates in Mauritius are highest for women up to 30 years of age, with the gap between female and male participation increasing with age. However, the female participation rate remains around two-fifths lower than for men and thus well below the world average. The ratio of female to male labor force participation in Mauritius is also 14 percentage points lower than for other upper-middle-income countries.

Figure 9.17.Labor Force Participation in Mauritius, 1990–2013

Sources: World Bank, World Development Indicators; and International Labour Organization.

Mauritius may be facing the middle-income female labor force participation challenge: at lower levels of income per capita, work may be a necessity in the absence of social protection programs, whereas women at higher levels of income can withdraw from the market in favor of household work and childcare. At advanced-economy income levels, labor force participation generally rebounds as a result of better education, lower fertility rates, access to labor-saving household technology, and the availability of market-based household services (Duflo 2012; Tsani and others 2012; World Bank 2011).

Most of the factors triggering a rebound in female labor force participation are present in Mauritius, particularly concerning education (Figure 9.18). Fertility rates are below the average for high-income countries, and there are no gender gaps in education—that is, primary and secondary school enrollment rates are virtually the same for boys and girls. Moreover, girls outperform boys in primary and secondary education; in particular, they are less likely to repeat a class than their male peers and more likely to complete the higher school certificate. In recent years, female tertiary enrollment rates have been higher than for males.

Figure 9.18.Labor Force Participation and Education in Mauritius

Sources: World Bank, World Development Indicators; and IMF, World Economic Outlook database.

Men represent the majority of those who are employed, but gender gaps vary across occupations. When employed, women are four times less likely to be entrepreneurs than men (Figure 9.19). The only employment category in which women are overrepresented is as contributing family workers, where they often contribute to businesses run by their husbands. Employed women work on average six fewer hours a week than men in all other occupations. Less than one-fifth of employers are female; accordingly, men are more than five times more likely to borrow to start or operate a business. Women also earn less in similar occupations, particularly in the primary sector or in self-employment. They are overrepresented among the poor and more likely to head poor households.

Figure 9.19.Gender Gaps by Occupation and Income in Mauritius

Unemployment is also higher among women than men (Figure 9.20). The largest share of unemployed women is between the ages of 16 and 30 years. One-fifth of unemployed women possess a tertiary education, and the percentage of those unemployed has increased significantly and faster for women than for men over the past five years. The Ministry of Labor explains low employment rates for women as a result of a male orientation of jobs in the business processing and textile sectors, with women often not willing to take such jobs because of odd hours of work and perceived bad working conditions. One-third of women looking for a job have no former work experience compared with one-fourth of men. When unemployed women do have work experience, it is most likely in trade or manufacturing.

Figure 9.20.Unemployment Rates by Age, 2005–14

(Percent)

Source: Statistics Mauritius.

Modeling the Implications of Gender Inequality for Growth

The general equilibrium occupational choice model by Cuberes and Teigner (2016) helps quantify the current GDP losses due to potential misallocations of women in the labor force. Agents are endowed with a random entrepreneurship skill that determines their optimal occupation (see also Chapter 3).2 Agents choose to work as either employers, self-employed, or workers. However, female labor market frictions prevent women from making an optimal choice among these activities. In particular, only a fraction μ of women can freely choose their occupation, while a share 1-μ is excluded from becoming an employer. Among those that cannot become an employer, only a fraction μ0 can choose to be self-employed. Finally, only a fraction λ can join the labor market in general, while a share of 1-λ of women is excluded from all occupations. These frictions may reflect discrimination, differences in the optimal choices of women, or other supply and demand factors. The parameters μ, μ0, and λ are chosen to match the ratio of female to male employers, female to male own-account workers, and the number of women and men in the labor force from 2004 to 2013.

The results of the calibration imply that Mauritius is losing out on a substantial share of GDP due to gender gaps in labor force participation. While losses implied by these three labor market frictions have declined since 2004, in line with a decline in the gender gap in labor force participation, the implied losses from gender gaps in labor force participation and occupation account still for more than 22 percent of GDP compared with a situation with no such gaps. Gender gaps in entrepreneurship have remained relatively stable, with implied losses of 6.6 percent of GDP in 2013, down only slightly from 7 percent in 2004.

Gender gaps and occupational choices vary strongly by age group (Figure 9.21). Occupational choices across age groups vary substantially as well. Following Cuberes and Teigner (2016), the GDP losses from labor force participation and occupational choices are calculated for different age cohorts. The relative contribution to the GDP loss depends on the size of the gap in labor force participation and occupation in a given age group but also on the size of this group relative to the total population. The results imply that the cohort between ages 35 and 44 accounts for about 31 percent of the losses from overall participation gaps and 36.5 percent of the losses from entrepreneurial gaps.

Figure 9.21.Mauritian Gender-Gap-Related GDP Losses by Age Group, 2004–13

(Percent)

Source: IMF staff estimates.

Closing gender gaps in labor force participation and occupation could mitigate the effects of projected demographic changes on growth. To model the implications of a shrinking workforce, the model is augmented by a restriction on both male and female workforce to capture the increase in the dependency for men and women over time. Figure 9.22 uses the United Nations Population Division’s medium fertility population projections and projects four scenarios for the evolution of gender gaps:

  • No change scenario—Gender gaps in labor force participation and occupational choice are set at their 2004–13 average, and the size of the working of the population contributing to production is projected to shrink in line with the projected change in the dependency ratio. The projected loss in GDP compared with a situation with constant dependency ratios would be almost 7 percent by 2035, about 16 percent by 2065, and more than 19 percent by 2100.

  • Participation adjustment scenario—Gender gaps fall by about 2 percent a year (in line with the average decline observed during 2004–13). This development could mitigate the GDP losses from rising dependency ratios to 1 percent in 2035, about 6.5 percent in 2065, and less than 7 percent in 2100.

  • Participation and occupation adjustment scenario—In addition to the assumptions in the previous scenario, the occupational gender gaps also decline by about 2 percent a year on average in this scenario. The GDP losses from the shrinking labor force would be overcompensated by the close in the gender gaps until 2055, and GDP losses afterward would remain small (less than 2 percent by 2100).

  • Immediate adjustment scenario—In this scenario, gender gaps close instantly, resulting in GDP gains of double-digit percentages GDP gains until 2055 and continued gains in the long term.

Figure 9.22.Mauritian GDP Losses under Different Gender Gap Scenarios

(Percent of GDP loss; medium-fertility assumption)

Finally, the impacts on GDP vary substantially with different assumptions about fertility (Figure 9.23). The net effect of changes in dependency ratios and a gradual adjustment of gender gaps in labor force participation and occupation (the third scenario) vary according to the assumptions on fertility. In the low-fertility scenario, gains in GDP per capita would initially increase because low fertility decreases the dependency ratios. Over time, however, these gains decrease and turn negative because lower fertility rates also imply a smaller working-age population after some time. The dynamics are reverted with lower bounds for the high-fertility scenario. The effects under the constant- and medium-fertility scenarios are broadly similar, with relatively small variations if gender gaps are gradually closed.

Figure 9.23.Mauritian Gender-Gap GDP Losses under Various Fertility Scenarios

(Percent of GDP loss)

Determinants of Female Labor Force Participation and Employment in Mauritius

The determinants of female labor force participation are analyzed using microlevel household data. The approach follows Das and others (2015) as follows:

  • First, each individual’s expected wage is estimated according to:

  • In which w is the log of the monthly income from the main job, Z includes individual and household characteristics, such as age and age squared, dummy variables for educational attainment, marital status, and presence of children below age 16 and below age 4.

  • In the second step, the probability of being in the labor force is estimated as follows:

    In this equation, Li = 1 represents that the individual is in the labor force, w^ is the log of monthly wage, and X captures other individual characteristics, such as marital status, educational attainment, age and age squared, the presence of children under age 4 or under age 16 in the household, and the household’s total expenditure to proxy for total household income. Finally, P captures the influence of policies, such as awareness of the employment information center.

Tables 9.5 and 9.6 highlight the determinants of wage and the probability to participate in the labor force for women and men.

Table 9.5.Determinants of Mauritian Wages
Wages
FemaleMale
Age0.0842***0.0777***
Age squared–0.0010***–0.0008***
Married0.01610.2557***
Children below age 40.0203–0.0013
Children below age 16–0.1282***–0.0362**
Less than primary education–0.3435***–0.3765***
Secondary education0.8178***0.5298***
Tertiary education0.6812***0.5198***
Constant6.8756***7.3609***
Number of observations569910135
Adjusted R-squared0.3700.317
Source: IMF staff estimates.Note: *p < 0.10; **p < 0.05; ***p < 0.01.
  • Wages—The gain from secondary education appears to be more than 50 percent larger for women than for men. Married men tend to have higher incomes, whereas marital status has no significant effect on women’s wages. The presence of children in the household is associated with lower wages for both men and women. However, the “wage penalty” is more than three times higher for women than for men.

  • Labor force participation—Household expenditure and age have a significant effect on whether both men or women join the labor force. Marriage decreases the probability that women will join the labor market, but it increases the probability that men will do so. There is a direct and positive effect of having young children in the household on men’s labor force participation, whereas children appear to impact women’s participation only through the effect on wages. The marginal effect of having a tertiary education is larger for women than for men. The examined factors explain less than 16 percent of the variation of participation for women but more than 35 percent for men, suggesting that other factors could also explain female labor force participation.

Several other factors constrain female labor force participation. About three-fifths of economically inactive women list homemaking activities as the main reason they do not join the labor force (Statistics Mauritius 2015), a reason barely mentioned for men. A lack of flexibility in working hours, the (un)availability of high-quality childcare, and the cost of childcare may also contribute. The Ministry of Labor suggests there also may be gender bias on the part of employers who may hold women’s reproductive role against them in their careers. In addition, women’s occupations are tilted toward “traditional” female occupations that are less valued in the labor market, and women are often not aware of training opportunities.

Policy Options

Several supporting policies are in place or have been adopted by the government:

  • Childcare—The government of Mauritius instituted one-time cash grants of up to $6,530 to existing childcare centers in 2013 and 2014. Companies with a Corporate Social Responsibility Fund can contribute monthly up to $50 to the cost of nurseries and kindergartens for the children of employees with a monthly basic salary of up to $390.

  • Maternity leave and protection—The duration of maternity leave has been extended from 12 to 14 weeks. Employers must fully pay for two weeks of leave in the case of miscarriage, independent of the employee’s length of service. Employers cannot give a notice of dismissal to women on maternity leave, and employment cannot expire during this time, except in the case of redundancy.

  • Child benefits—The maternity allowance has been standardized to 3,000 Mauritian rupees (MUR) (about $85) across sectors, from the previous range of MUR 300 to 2,000 (about $9–$56). The limit of payments to a maximum of three children in certain industries is gradually being removed.

  • Training opportunities for women—These are offered in several areas, including the manufacture of jute products, food catering, garment making, agro-processing, and information and computer technology.

  • Gender budgetingBox 9.1 gives an overview of the milestones achieved by the Mauritian government concerning gender budgeting.

  • Support to female entrepreneurs—About 5,000 women are currently registered with the Women Economic Council, which provides capacity-building services such as writing a business plan and preparing for interviews.

Box 9.1.Gender Budgeting in Mauritius

Government budgets and fiscal measures can be useful tools for promoting women’s development and gender equality. Budgeting at the local, state, and/or national level using a gender lens allows governments to identify important gender issues and allocate resources to address gender gaps or development goals. Gender budgeting originated in Australia in the 1980s and by the 1990s had spread to South Africa, Canada, and the United Kingdom and has now been applied in some form in more than 80 countries, including Mauritius.

Mauritius does not produce a separate budget for women but instead analyzes public expenditures and revenues from a gender perspective and identifies budgetary impacts for women and girls compared with men and boys. Since the start of gender budgeting in Mauritius in 2000, eight pilot ministries have formulated sector-specific gender policies: (1) Education, Culture, and Human Resources; (2) Youth and Sports; (3) Labor, Industrial Relations, and Employment; (4) Women’s Rights, Child Development, and Family Welfare; (5) Finance and Economic Empowerment; (6) Social Security, National Solidarity, and Senior Citizens Welfare and Reform Institutions; (7) Agro-Industry, Food Production, and Security; and (8) Civil Service and Administrative Reforms. Mauritius produces a National Gender Policy Framework as a way to recognize past achievements and promote future work toward gender equality and women’s empowerment. Figure 9.1.1 shows a timeline of key milestones in Mauritius’s progress.

Figure 9.1.1.Gender Budgeting Timeline in Mauritius1

Prepared by Lisa Kolovich.

Three employment programs work to mitigate skills mismatches in the labor market for both men and women.3

  • The newly introduced Back to Work Program places women over age 30 in a job for a period of six months with the payment of a stipend of MUR 5,000 (about $141) and the opportunity for training in a registered institution. Employers are refunded the training cost up to a maximum of MUR 7,500 (about $211) per woman and the stipend for the placement period.

  • The Youth Employment Program places unemployed men and women between ages 16 and 30 in an enterprise with training for one year, with a possible additional year in another enterprise. The government refunds 50 percent of the monthly stipend (for nongraduates MUR 6,000–8,000, and for graduates MUR 10,000–15,000—or about $282 to $423) and up to MUR 7,500 of training costs to the employer.

  • The Dual Training Program allows unemployed Mauritians to follow a diploma or degree course with a tertiary institution in fields required by the labor market while at work in an enterprise. The government refunds the monthly stipend of MUR 3,000 for a maximum of three years and the annual course fees up to 40 percent or MUR 45,000 (about $1,268), whichever is lower.

These measures are welcome and should be continued. Others could be expanded or complemented by additional policies:

  • Childcare—Continuing to increase the availability and affordability of quality childcare would help boost female labor force participation, but the design of such services is critical. In line with previous initiatives, the authorities should continue measures to upgrade all childcare centers to minimum quality standards.

  • Maternity leave and protection—Longer maternity leave increases female labor force participation, but only if it is not too long. The 14 weeks provided in Mauritius appears to be in the range of positive effects. However, if fully paid by the employer and unaccompanied by additional measures, maternity leave can bias the hiring decisions toward men. The government could consider extending parental leave to fathers, for example, by extending the total time of parental leave if a certain part is taken by the father.

  • In-work tax credits—These benefits can increase labor force participation by individuals with lower incomes and thus stimulate female labor supply. These in-work tax credits could be phased out as incomes rise to continue the marginal benefit of entering or staying in the labor force.

  • Financial literacy—Continue and upgrade measures to provide training in financial literacy to micro-entrepreneurs, a large share of whom are women.

  • Flexible work arrangements—Promote these beyond current provisions for part-time work.

References

    Burn Teelock, N.2014. “Gender Equality, Child Development and Family Welfare.” Unpublished.

    Cuberes, D., and M.Teigner. 2015. “How Costly Are Labor Gender Gaps? Estimates for the Balkans and Turkey.” Unpublished.

    Cuberes, D., and M.Teigner. 2016. “Aggregate Effects of Gender Gaps in the Labor Market: A Quantitative Estimate.Journal of Human Capital10 (1): 132.

    Das, S., S.Jain-Chandra, K.Kochhar, and N.Kumar. 2015. “Women Workers in India: Why So Few among So Many?IMF Working Paper 15/55. International Monetary Fund, Washington.

    Duflo, E.2012. “Women Empowerment and Economic Development.Journal of Economic Literature50 (4): 105179.

    Elborgh-Woytek, K., M.Newiak, K.Kochhar, S.Fabrizio, K.Kpodar, P.Wingender, B.Clements, and G.Schwartz. 2013. “Women, Work, and the Economy: Macroeconomic Gains from Gender Equity.IMF Staff Discussion Note 13/10. International Monetary Fund, Washington.

    Gonzales, C., S.Jain-Chandra, K.Kochhar, and M.Newiak. 2015a. “Fair Play: More Equal Laws Boost Female Labor Force Participation.IMF Staff Discussion Note 15/02. International Monetary Fund, Washington.

    Gonzales, C., S.Jain-Chandra, K.Kochhar, M.Newiak, and T.Zeinullayev. 2015b. “Catalyst for Change: Empowering Women and Tackling Income Inequality.IMF Staff Discussion Note 15/20. International Monetary Fund, Washington.

    International Monetary Fund (IMF). 2015. “Inequality and Economic Outcomes in Sub-Saharan Africa.” In Regional Economic Outlook: Sub-Saharan Africa.Washington, April.

    Tsani, Stella, LeonidasParoussos, CostasFragiadakis, IoannisCharalambidis and PantelisCapros. 2012. “Female Labour Force Participation and Economic Development in Southern Mediterranean Countries: What Scenarios for 2030?MEDPRO Technical Report 19. European Commission, Brussels.

    United Nations. 2013. World Population Prospects: The 2012 Revision (DVD).Department of Economic and Social Affairs, Population Division, United Nations, New York.

    World Bank. 2011. World Development Report 2012. Gender Equality and Development.World Bank, Washington.

    World Economic Forum (WEF). 2014. The Global Gender Gap Report 2014.Basel: World Economic Forum.

We thank Lisa Kolovich for her contribution of Box 9.1.

The chapter uses data provided by Statistics Mauritius. The views expressed in this chapter are solely those of the authors and are not necessarily shared by Statistics Mauritius.

The model is based on the span-of-control framework in Lucas (1978), with the extension of self-employment as a possible occupational choice.

Information from the Ministry of Labor, Industrial Relations, Employment, and Training: http://www.mauritiusjobs.mu/read_news/VFZSUmR3PT0%3D

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