Abstract
Morocco: Selected Issues
Morocco: Implications of Gender Inequality for Growth1
This paper quantifies the effect of gender inequality in Morocco on growth, compared to groups of faster growing countries. It also estimates income losses due to low female labor force participation. The results highlight that closing overall gender gaps would help Morocco close its GDP per capita gap with benchmark countries in other regions by up to 1 percentage point. Simulations also show that gradually closing gender gaps in the labor force participation rate could lead to significant income gains over the long term. Policy recommendations to promote gender equality include investing in secondary education for women and in infrastructure, and reforming gender-discriminatory tax policies and laws.
1. A number of studies have highlighted the correlation between gender gaps and weaker growth (WEF 2014; Cuberes and Teignier 2015a; Elborgh-Woytek and others 2013; Gonzales and others 2015b; IMF 2015a). The relationship between gender gaps and growth can work through various channels. Having more women in the labor force increases the pool of talent that employers can hire as well as the number of potential entrepreneurs. This implies a more efficient allocation of resources, and hence higher productivity and growth (Cuberes and Teignier 2015a). Women are more likely to invest a larger share of their household income in the education of their children (Elborgh-Woytek and others 2013). Finally, gender inequality is related to income inequality, which in itself has been shown to be a drag on growth (Ostry and others 2014). An IMF study shows that the Middle East, North African, Afghanistan and Pakistan (MENAP) region could have gained $1 trillion in cumulative output—equivalent to twice the average real GDP growth during the past decade—if female labor force participation had narrowed the gender gap from triple to double the average for other emerging market and developing countries during the past decade (IMF, 2015b).
2. This paper assesses the impact of gender inequality on growth in Morocco. According to the United Nations gender inequality index, Morocco ranked 117th out of 155 countries—below other MENAP countries such as Tunisia (48), Algeria (85) and Jordan (102).2 This is a cause of concern for Morocco, since at the global level, countries with high gender inequality are poorer and grow more slowly (Figure 1). The paper will first provide an overview of trends in Morocco’s gender gaps over time and compared to peer countries. It will then estimate GDP losses due to gender gaps. Finally, it will discuss policies to reduce gender gaps in Morocco.
Gender Inequality Index and GDP per Capita
Citation: IMF Staff Country Reports 2017, 065; 10.5089/9781475583519.002.A001
Source: UNDP.A. Gender Gaps in Morocco
3. Much progress has been made in closing gender gaps in education enrollment but challenges remain, in particular in rural areas. The female to male enrollment ratio at the primary school level jumped from around 70 percent in the mid-1990s to 95 percent today, and the gender gap for the secondary and tertiary levels narrowed significantly, up to 85 percent and 90 percent respectively. Nonetheless, Morocco is being outperformed by other comparator regions (Figure 2). Similarly, gaps in the adult literacy rate have also narrowed, but Morocco is also being outperformed by peer countries. Moreover, these improvements have been driven by the urban areas, where gender gaps in primary and secondary education enrollment have narrowed significantly. In contrast, in rural areas, 60 percent of women are illiterate compared to 35 percent for men.
Education and Literacy in Morocco
Citation: IMF Staff Country Reports 2017, 065; 10.5089/9781475583519.002.A001
4. Gender gaps in the Moroccan labor market are particularly large. At 25 percent, the rate of women’s participation in the labor force is just at the average for the MENAP oil importers’ region and lags behind other countries at a similar income level (Figure 3). In addition, female labor force participation has been declining over the past decade, mainly driven by falling participation for women over 25 years of age (World Bank 2016). There are also disparities between the rural and urban areas in terms of labor force participation, with the gender gap being wider in urban areas (HCP 2015). However, rural women seem to function as a “shock absorber” for the economy as they participate in the labor market in greater numbers when the economy goes well but are the first to be excluded when there is a downturn (Verme and others 2014).
Female Labor Force Participation Gaps
Citation: IMF Staff Country Reports 2017, 065; 10.5089/9781475583519.002.A001
5. There are also some gender disparities in employment rates, in particular for educated and young women. While the rate of unemployment is only slightly higher for women than for men and similar for youth, educated women have a much higher unemployment rate than their educated male counterparts (Figure 4). Labor market mismatches and regulations are known to be impediments to employment in Morocco and their impact is more acute on women. Indeed, Angel-Urdinola and others (2016) show that high minimum wages and payroll taxes are associated with higher unemployment rates and lower formality rates in Morocco, especially among youth and women in Morocco. Low levels of education also limit the chances of these women to actively participate in the economy and forces them to work in low quality jobs (Figure 5).
Labor Force Participation and Employment Levels by Education and Gender
Citation: IMF Staff Country Reports 2017, 065; 10.5089/9781475583519.002.A001
Employment Trends by Gender and Sector
Citation: IMF Staff Country Reports 2017, 065; 10.5089/9781475583519.002.A001
B. Quantifying the Impact of Gender Gaps on Growth
6. Two different empirical approaches are used in this paper to assess the impact of gender gaps on the Moroccan economy. First, we decompose the differences in average real GDP per capita growth rates in Morocco and benchmark groups that can be explained by gender gaps between Morocco and these groups. Second, we use a general equilibrium occupational choice model to quantify potential GDP losses due to misallocations of women in the labor force.
Implications of gender inequality for growth
7. A growth regression helps quantify the effect of gender inequality in Morocco, compared to groups of faster growing countries. We estimate the impact of gender inequality on growth while controlling for the impact of variables such as initial income, investment, education, infrastructure, terms of trade, and institutional quality on growth following the approach taken in Hakura and others (2016, Annex 1). The sample consists of 103 countries from regions including MENA, LAC, SSA, and Asia, as well as selected advanced economies over the period 1990 to 2014. We estimate the following equation:
in which yi is GDP per capita, Xi captures explanatory variables aforementioned and εt is the error term. A robust two step GMM methodology allows us to control for endogeneity issues.
8. Consistent with previous studies, the results show that gender inequality has a negative impact on growth and this impact is more striking for countries in their early stages of development. Gender inequality is negatively related to growth for all countries (Annex 1). However, when the model includes gender and income inequalities, gender inequality appears to negatively impact growth for lower income countries only, including Morocco. One plausible explanation is that gender inequality in the early ages of development is high but this effect tends to decrease as the economy grows. In other words, different countries might exhibit different levels of gender inequality because they are at different stages of development (e.g., reverse causality).
9. We find that Morocco’s real GDP per capita growth could significantly benefit from lowering gender inequality. In a second step, we decompose the differences in average real GDP per capita growth rates in Morocco and four benchmark groups.3 The results of this approach reveal that in addition to large effects on growth from educational gaps, gender inequality can explain Morocco’s real GDP per capita shortfall compared to benchmark groups. Reducing gender inequality and improving education to the levels of the Asian, Emerging Europe and Latin American benchmark countries could boost real GDP per capita growth rates relative to these countries by 1 percent, 1.5 percent and 0.75 percent respectively (Figure 6).
Growth Differential Decomposition
Citation: IMF Staff Country Reports 2017, 065; 10.5089/9781475583519.002.A001
Sources: IMF, World Economic Outlook database; PRS Group; World Bank, World Development Indicators; and IMF staff estimates.Note: The estimated regression coefficients in the previous model are applied to the differences between the average values of the factors associated with growth for the past few decades for Morocco, MENA OI and Emerging European countries. A bar with a negative value denotes what share of the shortfall in Morocco’s growth is explained by a particular variable. The sum of all negative contributions exceeds the observed growth shortfall indicated in the chart because of the offsetting catch-up effect.MENA OI: Egypt, Jordan, Mauritania, Tunisia, Pakistan; Europe: Turkey, Bulgaria, Hungary, Ukraine, Romania; Asia: Korea, Singapore, Malaysia, Thailand, China; Latin America: Argentina, Bolivia, Colombia, Costa Rica, Dominican Republic, Ecuador, Mexico, Panama, Peru.Female labor force participation and growth
10. An occupational choice model is used to quantify the current income losses due to misallocations of women in the labor force. In particular, we use the general equilibrium occupational choice model by Cuberes, Newiak and Teigner (2016) in which agents are endowed with a random entrepreneurship skill that determines their optimal occupation.4 Agents choose to work as either employers, self-employed, or employees. However, female labor market frictions prevent an optimal choice of women between these activities.5 In particular, only a fraction μ of women can choose their occupation freely, while a 1- μ cannot become an employer. Out of those excluded from being 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 optimal choices of women, or other demand and supply factors (see Box 1). The parameters μ, μ0 and λ are chosen to match the ratios of female to male employers, female to male own-account workers and women to men in the labor force.
Drivers of Female Labor Force Participation in Morocco
There are important regionally specific factors such as history, religion, and culture, as well as social norms that explain the low level of female labor force participation in the MENA region (World Bank 2012). In the case of Morocco, several papers (Verme and others 2014, World Bank 2015) have argued that the slow pace of growth—coupled with factors such as marriage, education, household composition, perceptions of the role of the women in the household, and society’s values regarding gender issues—tend to influence labor force participation. Verme and others (2014) highlight that the slow pace of structural transformation has not allowed sufficient creation of manufacturing jobs where women with a secondary school education could be employed. Marriage and household composition also influence the probability of participation. Educated women are likely to marry educated men who have done better than women in the labor market and may be able to support their families on their own. The probability of participation decreases with the number of children below six in urban areas.
11. The results show that Morocco is currently losing out on a significant share of income due to gender gaps in the labor market. The costs associated with gender gaps in labor force participation and entrepreneurship are currently as high as 46 percent of income per capita compared to a situation where women have the same level of labor force and entrepreneurship participation as men.
12. Reducing gender gaps would also help offset the impact of the demographic transition on growth (Figure 7). Morocco is in the midst of a demographic transition, leading to an increase in the working age population. However, population growth is slowing, and the United Nations population division projects a rise in the dependency ratio by 2040.
Demographic Transition in Morocco
Citation: IMF Staff Country Reports 2017, 065; 10.5089/9781475583519.002.A001
Simulating the implication of an increase in the dependency ratio for men and women suggests that policies to eliminate gender gaps could offset those negative effects. This in turn may lead to overall income gains of about 27 percent in 2040 if gender gaps are closed in 50 years (Figure 7).6
C. Policy Considerations
13. Morocco has implemented several policies to reduce gender inequality:
Legal framework. There are several laws in Morocco that promote gender equality, including the (revised) Labor Code (2004),7 the 2011 Constitution, which provides for equality for Moroccan citizens, and the family code, which was revised in 2004 with a view to expanding the rights of women in areas such as guardianship, marriage, child custody, and access to divorce.
Gender budgeting. Morocco is notable for having the first and most developed gender budgeting initiative in the Middle East and Central Asia region. Box 1 gives an overview of Morocco’s achievements in this area.
Maternity leave and protection. Morocco increased maternity leave in 2004. It now offers 14 weeks of maternity leave, at 100 percent of a woman’s wages, payable from a national social security fund, thereby meeting the ILO standards on duration of maternity leave.
Gender Budgeting in Morocco
Fiscal policies can play an important role in promoting gender equality and women’s development. Gender budgeting allows fiscal authorities, at any level of government, to assess the needs of men and women; identify key outcomes or goals; plan, allocate, and distribute public funds; and monitor and evaluate achievements. More than 80 countries have introduced gender budgeting initiatives. While the focus for most countries tends to be on using spending policies to address gender inequality, some countries have introduced changes to tax policies. Gender budgeting may emphasize administrative changes to expenditure tracking and monitoring systems.
Morocco is notable for being a precursor in introducing gender budgeting initiative in the Middle East and Central Asia region. Beginning in 2002, Morocco’s early efforts in gender budgeting focused on meeting the Millennium Development Goals, increasing women’s public employment, and collecting gender-disaggregated data. One of the cornerstones of Morocco’s effort is its annual Gender Report, published by the Ministry of Economy and Finance. The report now covers more than 30 departments and ministries and highlights key gender equality goals and recent accomplishments; in addition, some ministries report sectoral- and gender-disaggregated data.
Morocco has also taken steps to enshrine gender budgeting in its legal framework. The Council of Government approved in 2014 an organic finance law with two key components designed to strengthen the initiative. First, the law requires that gender equality be considered when defining performance objectives, results, and indicators in all line budgets. Second, the law dictates that the Gender Report be included as part of each year’s Finance Bill (UN Women 2014a). The latest Government Plan for Equality calls for strengthening this law by increasing transparency, improving fiscal performance, and generalizing evaluation, audit, and accountability procedures (Ministry of Economy and Finance of Morocco 2013).
Stotsky (2016) summarizes key components found in the most successful gender budgeting efforts and, typically, these efforts are led by the ministries of finance and have support from parliaments and/or NGOs. In addition, successful gender budgeting initiatives often tie their gender equality targets to the Millennium Development Goals or a national development strategy and establish a legal basis for gender budgeting. Morocco’s effort includes all of these components. There is however scope to increase the role of parliament or civil society organizations in Morocco’s gender budgeting work.
14. While these measures are welcome and should be continued, some could be expanded or complemented by additional policies, such as:
Legal restrictions. Providing for equality in inheritance rights can create opportunities for women to own housing or land (World Bank, 2015) and lead to smaller gender gaps in labor force participation (Gonzales et al, 2015a). There are several areas where legal inequalities remain. Married women are not permitted to be the head of the household. There is also inequality between sons and daughters and between female and male surviving spouses in their rights to inherit assets.
Paternity leave. Increasing paternity leave, which is currently one of the lowest in the world (3 days) could contribute to gender equality at work and intra-household equality.
Infrastructure. Safe public transportation and improved road accessibility would decrease women’s travel time and therefore reduce the costs related to work and going to school outside the home (World Bank, 2016). Investing in public childcare facilities could free women’s time to go to school and join the labor market, since women are in most cases the main providers of household work in Morocco.
Gender budgeting. Morocco could enhance the oversight, audit, and monitoring of its gender budgeting efforts, as there is currently no comprehensive system in place for monitoring or evaluation.
Remove gender discriminatory tax practices. There are several areas where Morocco has discriminatory tax policies (World Bank, 2015). Morocco is one of 17 out of 189 countries that has tax deductions or credits that are specific to men: a male taxpayer is able to claim a dependent deduction for both his spouse and children, but unless a female taxpayer is able to prove that she is a legal guardian, she may not claim the same deduction.
Education and employment. The national employment strategy has several recommendations to promote equity in education, as well as to raise female labor force participation, which needs to be followed by specific measures. In particular, it recommends: (1) using the current conditional transfers for education (Tayssir) to promote better access to secondary education for girls; (2) literacy programs for women in rural areas and vocational training programs for all women; (3) creating more local jobs, especially in activities which require more women; and (4) supporting female entrepreneurship.
Annex I. Growth Effects of Gender Inequality
Methodology
1. The equation set to be estimated is given by:
in which yi is GDP per capita growth, and Xi captures explanatory variables including gender and income inequality measures, the log of initial GDP, investment, education, infrastructure, terms of trade, institutional quality, and a dummy variable set to capture periods of high inflation. A problem that often occurs when dealing with growth models is the endogeneity issue. IV techniques, to address endogeneity, suggest the use of instruments that are uncorrelated with the error term but partially and sufficiently linked with the corresponding explanatory variable. The main issue rising with this method is the difficulty of finding proper instruments. The GMM method—which is the method adopted in this study—is useful for its simplicity in dealing with endogeneity issues.
Data
2. The selected factors influencing GDP per capita growth are given by: the initial income per capita measured by the log of GDP per capita, investment captured by the fixed capital formation as a percentage of GDP, education measured by the total average years of schooling, a dummy capturing periods of average inflation of 15 percent and above, an index capturing institutional quality (typically this index captures the quality of politics in the country; essentially a higher coefficient means better institutional quality), and an infrastructure index compiled using the first principle component analysis with variables including mobile phones and internet per 100 people, access to electricity and water, and total air transportation of passengers per year. This equation is augmented with various measures of inequalities for robustness checking purposes. Income inequality is captured by three measures including the ratio of income held by the richest 20 percent of the population relative to the poorest 40 percent, and the net Gini coefficient. Gender inequality on the other hand is mainly captured by the UN’s gender inequality index (GII). This index is a combination of various gender gaps in terms of opportunities and outcomes.
3. The sample consists of 103 countries from regions including MENA, LAC, SSA, and Asia as well as selected advanced economies over the period 1990 to 2014. All the variables are averaged over a five-year period except for the net Gini coefficient for which the first value of the five years is taken into account; that of the previous year when data is missing. The estimation technique used is a robust two step system GMM method.
Estimation Results
Baseline Model
Baseline Model
| (1) | (2) | (3) | |
|---|---|---|---|
| Initial income per capita (log) | − | −1.606*** | −1.801*** |
| Infrastructure index | 1.595*** | 0.435** | 0.103*** |
| Institutional quality | 0.555** | 0.137*** | 0.279* |
| Measures of inequality | 0.129** | ||
| Share top 20 to bottom 40 ratio | 0.0001 | ||
| Share top 20 to bottom 40 ratio x LICs | − | ||
| Initial income inequality (net GII) | 0.235*** | −0.002 | |
| Initial income inequality (Net Gini) xLICs | −0.033** | ||
| Gender inequality | −0.036** | ||
| Gender inequality xLICs | −0.028*** | ||
| Constant | 1.902 | 2.728 | 9.755*** |
| Number of instruments | 9 | 8 | 8 |
| Arellano-Bond AR(1) (p value) | 0.006 | 0.003 | 0.001 |
| Arellano-Bond AR(2) (p value) | 0.027 | 0.025 | 0.085 |
| Sargan (p value) | 0.249 | 0.700 | 0.278 |
| Hansen (p value) | 0.520 | 0.691 | 0.387 |
| Observations | 380 | 450 | 369 |
| Number of countries | 97 | 97 | 97 |
Baseline Model
| (1) | (2) | (3) | |
|---|---|---|---|
| Initial income per capita (log) | − | −1.606*** | −1.801*** |
| Infrastructure index | 1.595*** | 0.435** | 0.103*** |
| Institutional quality | 0.555** | 0.137*** | 0.279* |
| Measures of inequality | 0.129** | ||
| Share top 20 to bottom 40 ratio | 0.0001 | ||
| Share top 20 to bottom 40 ratio x LICs | − | ||
| Initial income inequality (net GII) | 0.235*** | −0.002 | |
| Initial income inequality (Net Gini) xLICs | −0.033** | ||
| Gender inequality | −0.036** | ||
| Gender inequality xLICs | −0.028*** | ||
| Constant | 1.902 | 2.728 | 9.755*** |
| Number of instruments | 9 | 8 | 8 |
| Arellano-Bond AR(1) (p value) | 0.006 | 0.003 | 0.001 |
| Arellano-Bond AR(2) (p value) | 0.027 | 0.025 | 0.085 |
| Sargan (p value) | 0.249 | 0.700 | 0.278 |
| Hansen (p value) | 0.520 | 0.691 | 0.387 |
| Observations | 380 | 450 | 369 |
| Number of countries | 97 | 97 | 97 |
4. The results robustly reveal that, in line with prior expectations, inequalities have a negative impact on growth. This is especially important for countries in their early stages of development.
5. Income inequality is confirmed to significantly and robustly impede growth for low income countries for the Gini coefficient and the ratio of income share held by the top 20 percent richest segment of the population relative to the bottom 40 percent. For the latter, in model specification (4) which accounts for both gender and income inequality, the impact remains negative and this is so regardless of whether the focus is shifted to the entire sample.
6. Furthermore, gender inequality is also negatively related to growth as reported by model specification (3) for the whole sample. However, in model specification (4), gender inequality appears to significantly and negatively impact growth for low-income countries alone. This result in model specification (4) further consolidates the theoretical idea that gender inequality in the early ages of development is high but decreases as the economy grows.
Estimation Results
Estimation Results
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| Measures of inequality | ||||
| Share top 20 to bottom 40 ratio | −0.040 | −0.116** | ||
| Share top 20 to bottom 40 ratio x LICs | −0.129* | |||
| Initial income inequality (net GII) | 0.006 | |||
| Initial income inequality (net Gini) | −0.022** | |||
| xLICs | ||||
| Gender inequality | −0.039** | −0.003 | ||
| Gender inequality xLICs | 0.0005 | −0.019** | ||
| Female legal equity xLICs | −0.031 | |||
| Other control variables | ||||
| Initial income per capita (log) | −1.267*** | −1.438*** | −1.913*** | −1.421*** |
| Fixed capital investment (% GDP) | 0.131*** | 0.108*** | 0.084** | 0.103*** |
| Schooling (years) | 0.021** | 0.005 | 0.024** | 0.018** |
| Infrastructure index | 0.177 | 0.590** | 0.252 | 0.262** |
| High inflation | 1.277 | 0.064 | 5.496 | −0.738** |
| Institutional quality | 0.130*** | 0.089** | 0.178** | 0.063** |
| Constant | −2.018 | 0.207 | 1.321 | 5.115** |
| Number of instruments | 18 | 18 | 21 | 21 |
| Arellano-Bond AR (1) (p value) | 0.017 | 0.003 | 0.080 | 0.003 |
| Arellano-Bond AR (2) (p value) | 0.460 | 0.105 | 0.349 | 0.220 |
| Sargan (p value) | 0.106 | 0.165 | 0.284 | 0.118 |
| Hansen (p value) | 0.566 | 0.410 | 0.296 | 0.491 |
| Observations | 380 | 450 | 369 | 234 |
| Number of countries | 97 | 97 | 97 | 70 |
Estimation Results
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| Measures of inequality | ||||
| Share top 20 to bottom 40 ratio | −0.040 | −0.116** | ||
| Share top 20 to bottom 40 ratio x LICs | −0.129* | |||
| Initial income inequality (net GII) | 0.006 | |||
| Initial income inequality (net Gini) | −0.022** | |||
| xLICs | ||||
| Gender inequality | −0.039** | −0.003 | ||
| Gender inequality xLICs | 0.0005 | −0.019** | ||
| Female legal equity xLICs | −0.031 | |||
| Other control variables | ||||
| Initial income per capita (log) | −1.267*** | −1.438*** | −1.913*** | −1.421*** |
| Fixed capital investment (% GDP) | 0.131*** | 0.108*** | 0.084** | 0.103*** |
| Schooling (years) | 0.021** | 0.005 | 0.024** | 0.018** |
| Infrastructure index | 0.177 | 0.590** | 0.252 | 0.262** |
| High inflation | 1.277 | 0.064 | 5.496 | −0.738** |
| Institutional quality | 0.130*** | 0.089** | 0.178** | 0.063** |
| Constant | −2.018 | 0.207 | 1.321 | 5.115** |
| Number of instruments | 18 | 18 | 21 | 21 |
| Arellano-Bond AR (1) (p value) | 0.017 | 0.003 | 0.080 | 0.003 |
| Arellano-Bond AR (2) (p value) | 0.460 | 0.105 | 0.349 | 0.220 |
| Sargan (p value) | 0.106 | 0.165 | 0.284 | 0.118 |
| Hansen (p value) | 0.566 | 0.410 | 0.296 | 0.491 |
| Observations | 380 | 450 | 369 | 234 |
| Number of countries | 97 | 97 | 97 | 70 |
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Prepared by Vincent Dadam, Lisa Kolovich, and Anta Ndoye. Gregory Auclair provided research assistance.
This index measures gender inequality of outcomes (the gap between male and female labor force participation rates and the share of women’s seats in parliament) as well as inequality of opportunity (gender gaps in education and indicators of female health, such as the maternal death ratio and adolescent fertility).
MENAP oil importers (Egypt, Jordan, Mauritania, Tunisia, and Pakistan), Asian countries (Korea, Singapore, Malaysia, Thailand, and China), Latin American countries (Argentina, Bolivia, Colombia, Costa Rica, Dominican Republic, Ecuador, Mexico, Panama, and Peru), and European countries (Turkey, Bulgaria, Hungary, Ukraine, and Romania).
The model is based on the span-of-control framework in Lucas (1978), with the extension of self-employment as a possible occupational choice and uses ILO data on occupation by gender.
This omits the possibility of women producing some type of good in the household sector or in the informal economy.
These gains in GDP decrease the longer it takes to eliminate gender gaps. For instance, the results show that GDP gains would be 13.6 percent if gender gaps were to be eliminated in 100 years, and 9.2 percent were they to be eliminated in 150 years.
In 2004, a new labor law went into effect in Morocco, offering greater protection for women in the labor market (such as restrictions on women’s working hours and types of jobs, mandatory leave and rest days, and time allowances for breast-feeding and childcare requirements).
