Chapter II HOW CAN BENIN’S DEMOGRAPHIC TRANSITION SUPPORT ECONOMIC GROWTH? Benin Country Economic Memorandum 2.0 ©2022 The World Bank 1818 H Street NW, Washington DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org Some rights reserved This work is a product of the staff of The World Bank. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of the Executive Directors of The World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Rights and Permissions The material in this work is subject to copyright. Because the World Bank encourages dissemination of its knowledge, this work may be reproduced, in whole or in part, for noncommercial purposes as long as full attribution to this work is given. The pictures should be attributed to Stephane Brabant unless otherwise specified. Attribution—Please cite the work as follows: “World Bank. 2021. Benin Country Economic Memorandum © World Bank.” All queries on rights and licenses, including subsidiary rights, should be addressed to World Bank Publications, The World Bank Group, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2625; e-mail: pubrights@worldbank.org. 2 ACKNOWLEDGEMENT The Country Economic Memorandum was prepared by a team led by Nathalie Picarelli and Xun Yan. The team included Alexandre Henry, Solene Rougeaux, Saint-Martin Mongan-Agbeshie, Felicien Towenan Accrombessy, Hasan Dudu, Jakob Engel, Besart Avdiu, Mathilde Lebrand, Daniel Alberto Benitez, Megersa Abera Abate, Marjan Petreski, Esther Maria Bartl, Houdou Romaric Samson, Lulit Mitik Beyene, Alejandro Sicra, Zhen Liu, Amevi Rocard Kouwoaye, Adam Levai and Noukpo Homegnon. The report was prepared under the overall guidance of Abebe Adugna, Coralie Gevers, Atou Seck and Theo David Thomas. Helpful advice, comments and data were received from Andrea Coppola, Michel Welmond, Susana M. Sanchez, Ernest John Sergenti, Fiseha Haile, Leif Jensen, Olivier Hartmann, Jean Michel N. Marchat, Anouk Pechevy, Jim Cust, Alexis Rivera Ballesteros, Gabriel Stefanini Vicente, and Sidikou Salihou Mamadou. And from peer reviewers Sona Varma, Ashley Taylor, Amina Coulibaly, Wendy Cunningham, Sara Troiano, Paul Brenton and Anne-Cecile Souhaid. Micky O. Ananth, Maude Jean-Baptiste and Benita Mahinou provided excellent administrative and operational assistance. Kartographia provided mobile data visualization support. 24Slides designed the report. Yao Gnona Afangbedji kindly provided photos and communications support. Fiona Hinchcliffe provided excellent editorial support. The team gratefully acknowledges the collaboration with the Beninese authorities, notably the Direction Générale de l’Économie (DGE), the Ministry of Economy and Finance, and the Institut National de la Statistique et de la Démographie (INStaD). The CEM reflects the discussions from a workshop with different stakeholders in Benin in December 2020. This report would not have been finalized without the generous financial assistance from the Umbrella Facility for Trade Trust Fund and NDC Climate Support Facility Trust Fund. The team is grateful to the Development Data Partnership for their data program with X-Mode through which data was made available. 3 TABLE OF CONTENTS Page / 003 Acknowledgement Page / 005 Acronyms and abbreviations Page / 006 Introduction Page / 010 Section 2.1: Reducing gender gaps Page / 020 Section 2.2: Enabling human capital accumulation Page / 027 Section 2.3: Improving the quality of the labor market Page / 042 Section 2.4: Policy options Page / 046 References Page / 049 Terms and definitions Page / 051 Appendix ABBREVIATIONS AND ACRONYMS Fonds de Développement de la Formation Professionnelle ALMP Active Labor Market Policy FODEFCA Continue et de l’Apprentissage ANPE National Jobs Agency, Agence Nationale Pour l’Emploi HCI Human Capital Index CEM Country Economic Memorandum LICs Low-income countries CFAF CFA Franc LMICs Lower-middle income countries CGE Computable General Equilibrium PP Percentage points COVID-19 Corona virus disease GDP Gross domestic product CPIA Country Policy and Institutional Assessment SMIG Minimum wage DTM Demographic transition model SSA Sub-saharan Africa ECOWAS Economic Community of West African States TFR Total fertility rate FNPEJ Fonds National pour la Promotion de l’Emploi des Jeunes TVET Technical and Vocational Education and Training FNRB Fond National des Retraites WAEMU West African Economic and Monetary Union FNM Fond National de Microfinance WB World Bank 5 Introduction How can Benin’s demographic transition benefit economic growth? Benin could benefit from its demographic transition. Currently, at 4.8 children per woman, its fertility rate is substantially higher than structural peers (4.3) and other sub-Saharan African (SSA) countries that are already further along their demographic transition (for example, many in Southern Africa). With a rapidly growing population, that has risen from 2.4 million in 1960 to close to 12 million in 2020, Benin is considered a pre-dividend country. With the right policies in place, it can take advantage of its growing young population to increase productivity and growth per capita. The speed at which its demographic transition takes place and the economic and human development policies that accompany it can power the next wave of economic growth, if healthier and better educated young people enter expanding labor markets. This is known as the demographic dividend – the accelerated economic growth that can arise from the increase in the share of the working-age population in the total population of a country. This youth bulge may result in economic dividends derived from changes in labor supply, savings, and human capital. A large working-age population means that more people have the potential to be productive and contribute to economic growth (World Bank 2016). More important for a sizable dividend are changes in worker productivity. Smaller family sizes mean that both families and governments have more resources to invest in health and education per child. With more resources and reduced expectation on childbearing, girls will be able to receive better and longer education and be prepared to enter the skilled labor force. 6 Many countries have experienced tremendous economic benefits of demographic dividends in the past decades. Countries in Europe and Asia were able to reap the economic benefits from their demographic transitions over the last century (Bloom et al 2010). Cross-country estimates suggest that an increase of 1 percentage point (pp) in the share of the working-age population can boost economic growth by 1.1–2.0 pp (Beegle and Christiaensen, eds. 2019). The causality underpinning this association is complex and occurs through multiple pathways, including an increase in the supply of workers relative to the total population; a rise in the capacity to save, which leads to a higher capital per worker ratio; and more investment in human capital. The extent to which a country can reap a demographic dividend varies and depends on policies (Box 2.1). For instance, the growth in productivity driven by the increase in the share of the working-age population will depend on the absorption capacity of the labor market. The quality of jobs – i.e., the levels of informality, stability of contractual employment practices, wage levels, and fit between education and work – also matters for achieving demographic dividends (Marone 2016). South Africa, for example, was the first country in SSA to start its demographic transition. Over the past three decades, the median age has substantially risen from 18 years to 25 years but socio-economic inequalities in the labor market have limited the gains from the demographic transition (Bruni, Rigolini, and Troiano 2015). On the other hand, countries in East Asia such as China, South Korea, Japan, and Singapore were able to benefit from the decline in fertility rates in 1965-1990, as the increase in the working age was accompanied by policies able to expand per capita productive capacities. As a result, they experienced the highest growth rates of real income per capita (Bloom and Williamson 1998). Benin will only be able to reap the demographic dividend if adequate policies accompany the fertility decline of its demographic transition. Improvements in gender equality, quality investments in human capital, and a reform of the labor market will play important roles in ensuring that Benin’s demographic change contributes to economic growth. The chapter is organized as follows: Section 2.1 explores the importance of reducing gender gaps; Section 2.2 discusses the limitations to human capital accumulation; Section 2.3 presents the weaknesses of labor markets while Section 2.4 outlines policy options. 7 Introduction Box 2.1 When does the demographic dividend happen? The demographic transition model (DTM) describes the transition of populations from high to low fertility and mortality rates. The model consists of at least four distinct phases, with countries effectively moving from high B1 Stages of demographic transition fertility and low life expectancy to low fertility and high life expectancy as they move through the demographic transition. At the same time, they go from high proportions of children and few elderly to low proportions of children and many elderly. Fertility rates and mortality rates are both high in the first stage. If mortality rates fall but fertility rates remain high, as in the second phase, population growth accelerates, with growing numbers of young and rising youth dependency (pre-dividend societies). The third stage, during which the demographic dividend may take place, is catalyzed by a decline in total fertility rates (TFR), leading to a smaller dependency ratio. To spark this phase, human development outcomes – especially in health and education – must improve and gender gaps must be closed. During this phase, the labor force temporarily grows more rapidly than the dependent population. The creation of productive jobs for the growing share of the working age population is necessary at that stage, together with further investments in human capital and greater integration of youth and women in labor markets. At the same time, as the share of the working-age population increases, resources can be freed up for Stages: I II III IV investment in human capital such as health and education. Consequently, per capita income grows more rapidly, everything else being equal. The fourth phase includes a possible second demographic dividend that can result from the savings and Source: World Bank 2016 and author’s adaptation investments as the bulge cohort matures and saves for retirement. As in other stages of the transition, this is only possible with adequate policies. This time, policies should promote savings and financial sector deepening so as to translate them into productive investments. Savings must be sufficient to finance the cohort’s retirement and health care needs. Source: Lee and Mason 2006, World Bank 2016. 8 Introduction Though declining, fertility rates are still higher than peers’ Benin still needs to undergo its The share of commodities in the demographic transition TFR has been declining over the last two A 01 export decades… B 02 …but …but it remains remains above much most higher peers than peers basket has declined over time… In 2018, the total fertility rate (TFR) was 4.8 in Benin, more than Growth in total fertility rates (2000-2018) Total fertility rates in 2018 double the replacement rate (2.1). It was also much higher than that of structural peers, and substantially above aspirational peers like Sri Lanka Morocco 4.8 Morocco and Sri Lanka that are more advanced in their demographic Rwanda 4.6 Senegal 4.3 Ghana 4.0 Benin 3.9 Togo transitions. In 2019, the adolescent fertility rate was only higher in Togo 2.4 2.2 (89 births per 1,000 girls aged 15-19). While TFR has been declining -2% during the last two decades, the decline has been slower than in all structural peers except Senegal. -13% While fertility rates are still high, Benin’s demographic transition Morocco Togo Ghana Sri Lanka Senegal Rwanda Benin -15% -19% -20% -20% has already started due to a decline in mortality rates. Benin’s -28% death rate has declined rapidly in the past 60 years, from 28.8 deaths Source: WDI and Authors’ calculation Source: WDI and Authors’ calculation per 1,000 in 1960 to 8.9 per 1,000 in 2018. Benin’s population will grow rapidly if fertility does not decline. Openness Adolescentto services fertility exports rates is lower still contribute Population will grow rapidly if TFR does With constant fertility, population projections show that Benin’s C 03 D 04 Net FDI inflows remain below peers than all peers substantially (2011-2018) to Benin’s high TFR not decline population will grow from around 12 million in 2020 to 124 million in Adolescent fertility rates in 2019 Medium variant High variant 2100. A reduction in fertility rates can lead to a substantial slowdown in Benin’s population growth (see assumptions). A scenario involving a 88.7 Low variant Constant-fertility 84.0 decline in fertility to 2.3 children per woman in 2100 would lead to a 70.7 65.8 150 000 population of 47.2 million. In comparison, if Benin’s fertility declined to 38.9 2.8 children per woman in 2100, the population would reach 64.2 30.7 100 000 20.7 million. A fertility reduction to 1.8 children per woman would lead to a 50 000 population of 33.8 million. Without a decline of fertility rates (Appendix 2), the higher burden on the working population will further strain the Togo Ghana Morocco Senegal Sri Lanka Rwanda Benin 0 provision of health and education services. 2080 2020 2030 2040 2050 2060 2070 2090 2100 See more: How does Benin compare to early-dividend sub-Saharan countries? (Appendix 3). Source: WITS and authors’ calculations Source: United Nations Department of Economic and Social Affairs, UN Population Division 9 Introduction REDUCING GENDER GAPS IS CRUCIAL TO SUSTAIN 2.1 THE DEMOGRAPHIC TRANSITION Gender gaps in social and economic opportunities remain large and have improved little during the last two decades. Closing gender gaps should have a major impact on reducing fertility rates and supporting the demographic transition. This section builds on the Benin Gender Assessment (World Bank 2021). Gender gaps in economic opportunities are discussed in Section 2.3. 10 2.1.1 Large gender gaps in human development outcomes could undermine the demographic transition Benin ranks 158 out of 189 countries in the Gender Development In 2021, Benin ranked 123 out of 156 countries in the Gender Gaps Index (GDI), placing it below most structural and aspirational peers Report. It ranked bottom for educational attainment and political with the exception of Togo and Morocco. empowerment and was below peers’ median for health. 05 Gender Development Index (2019) 06 Gender Gaps (2021) Gender gaps Economic opp. Education Health Political empowerment 0.955 200 0.945 0.911 150 150 0.870 131 0.855 123 0.835 0.822 100 70 50 9 Togo Ghana Morocco Sri Lanka Senegal Rwanda Benin 0 Benin Morocco Ghana Togo Senegal Sri Lanka Rwanda Source: UNDP 2020, Notes: The GDI measures gender gaps in human development achievements by accounting Source: WEF 2021; Note: Progress towards gender parity (first column in the chart) is benchmarked in four for disparities between women and men in three basic dimensions of human development —health, knowledge dimensions: economic opportunities, education, health and political leadership. The higher the rank the greater and living standards. The index measures the performance in gender development with is a metric ranging the gender inequalities. Economic opportunities are curtailed due to the high participation estimates for both between 0.488 (worst) and 1.036 (best) in 2019. female and male in the region that do not account for quality of the labor market (see Section 2.3). 2.1.1 Large gender gaps in human development outcomes could undermine the 11 demographic transition Maternal and infant health Infant and maternal health lag behind peers A Benin’s maternal mortality is the Infant mortality is also slow to decline B …preventing Benin from catching up with peers 07 highest of its peers (2000-2017) 08 (2000-2019) Birth and death rates determine the natural growth of a population. As such, mortality and fertility have direct effects on age structure, defining the share of working-age individuals, children, and Sri Lanka Sri Lanka Morocco Morocco Rwanda Rwanda Senegal Senegal Ghana Ghana Benin Benin elderly in the total population, which affects a country’s capacity to Togo Togo 0% 1400 0% 120 produce, invest and save (Ahmed et al 2016). Herzer et al (2012) and -20% 1200 100 Angeles (2010) suggest that reductions in fertility rates are mostly -24% -19% 1000 -20% 80 driven by a decline in mortality rates as lower mortality (especially -40% -36% -36% 800 infant mortality) reduces the desire for more childbearing, lowering -40% -31% 60 -60% -43% 600 -39% the potential fertility rate. -47% 40 -80% -63% 400 -60% -52% -56% -57% 20 In Benin, maternal and child mortality have declined, but more -79% 200 slowly than for structural and aspirational peers. Starting almost -80% 0 -100% 0 -75% at the same level, maternal mortality has declined slowly during the Source: World Development 2020. Note: Maternal mortality (per 100,000 live births, modeled estimate) over the period Source: World Development Indicators 2020. Note: rate of under 5-year-olds (per 100,000 live births) over the period last two decades. Since 2010, Senegal and Rwanda have seen their 2000-2017. Levels right axis, (2000-2017); and 2017 levels in red. 2000-2019. rate decline by one third, while it only dropped by 14% in Benin. Similarly, infant mortality declined by 31%, significantly lower than in C Labor 09 productivity Gender equality contributed less than and maternal peers to mortality in per IDA capita & IDA growth blend countries is negatively correlated peers, albeit starting at a higher level (Figure 4b). 1400 High levels of infant, child and maternal mortality reflect gender Maternal mortality ratio 1200 inequalities. Low levels of education for women partly limit the 1000 ability to make informed health care decisions, control over financial (2010-2017) 800 resources, and mobility to access health care services –all factors which may prevent women from receiving the quality of care essential 600 Benin for ensuring healthy pregnancies and deliveries (UNICEF). Too many 400 women in SSA die from (often preventable) conditions during 200 pregnancy and childbirth (Beegle and Christiaensen, eds. 2019). 0 Reducing gender inequalities in accessing human capital will improve 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00 infant and maternal health. CPIA gender equality (2000-2019) Source: WDI, CPIA and Authors’ calculation CPIA on gender equality is a metric ranging from 1 (worst performance) to 5 (best performance) 2.1.1 Large gender gaps in human development outcomes could undermine the 12 demographic transition Gender gaps in education in Benin Gender gaps in education are declining but still large A Women are more likely to be illiterate While gender gaps in primary school B …preventing Benin from catching up with peers 10 than men 11 have been closing… Female education is the most important single factor for reducing the TFR. Research shows a fairly robust causal relationship Literacy levels 2018 Language skills at the end of primary school between women‘s education and fertility decline. More-educated 100 589.1 582.7 women delay their first marriage and have greater income 80 600 60 opportunities (DeCicca and Kashinsky 2016) which increases the 40 550 opportunity cost of not participating in the labor market, leading to 20 520.1 527.1 delayed or fewer births (Bloom et al. 2009). At the same time, better 0 500 education reduces maternal and infant deaths. Only 71% of women Urban Female 15-24 25-34 35-44 45-54 55-64 Male Rural with no education in Benin are helped to give birth by a skilled 450 attendant, compared to 84% for those with primary education. Total Sex Area Age 2014 2019 Girls' score Boys' score There are substantial gender gaps in education. Half of Benin's Yes No population was literate in 2018: 70% of men compared to only 40% of Source: EHCVM2018 and Authors’ calculation. Note: literacy is measured as share of literate population in respective population Source: PASEC 2016 and 2020. Note: average differences in scores for boys and girls for 2014 and 2019 at the beginning and end of primary school. Unit is score level adult women. While women’s literacy has improved substantially group. from 1 to 600. since 2012 – when it was 22.1% – it remains below all structural peers. The literacy rate for adult women reached 70% in Rwanda and more C Labor 12 productivity …significant contributed gaps remain inless than peers secondary to per capita growth schooling than 50% in Togo in the same year. Gross enrolment rates (in percentages) The gender gap in education is shrinking for younger generations. In 2018, there was only a 13.5 pp gap in literacy rates 150.00 betwee15- to 24-year-olds, compared to a 28-pp gap for those 100.00 between 25 and 34. The closing gaps are driven by increased access 50.00 to primary education. Girls’ language scores in standardized national 0.00 tests improved by 70 points between 2014-2019, compared to a 55- point improvements for boys in the same period. Gaps remain large 2015 2000 2005 2010 2018 2000 2005 2010 2012 2015 2018 2000 2004 2015 2016 2017 in secondary school due to early dropout. The intake rate for girls is Pre-schooling Primary Secondary 62% in lower secondary education compared to 70% for boys. Yet, Girls Boys completion rates are much lower with only 39% of girls completing, against 51% of boys. The difference between girls and boys becomes Source: WDI and authors’ calculation. Notes: The percentage above 100 means that the system has also enrolled the over - and under-aged population in primary education more pronounced in upper secondary education where girls’ institutions due to early or late schooling which also includes repeaters enrolment in the final grade is only 18% against 37% for boys (WB, Benin Global Partnership for Education Project). 2.1.1 Large gender gaps in human development outcomes could undermine the 13 demographic transition 2.1.2 Social norms perpetuate high fertility rates and gender inequalities Social norms are important determinants of high TFRs Due to social norms, the wanted fertility rate in 13 Benin has not declined Social norms and legal restrictions largely shape the agency of women and girls. Important life decisions about family, education, and Total fertility rate and wanted fertility rate health usually follow, directly or indirectly, from social norms prevailing (as births per woman) in one‘s society. As such, they are key factors underlying gender-based 7 differences in access to opportunity. For instance, traditional roles and associated time-use patterns constrain women’s economic 6 opportunities (Appendix 4), and more details in Section 2.3). In addition, 5 limitations in women’s and girls’ agency are often explained by other disadvantages, particularly in access to education. 4 Patriarchy is a social system in which men hold power and take on the 3 lead role in moral authority, political leadership, and social life (Lerner 1986). Patriarchal social norms give men socially accepted decision- 2 making authority over women‘s political, social, and economic lives. 1 Social norms in Benin’s patriarchal society promote families with many children. Children are commonly seen as an insurance for their 0 parents; and women’s primary role is seen to be marriage and 1996 2001 2006 2012 2018 childbearing. Even if not all women agree, financial dependence often Fertility rate, total (births per woman) Wanted fertility rate (births per woman) makes any deviation difficult (Benin Gender Assessment 2021). Source: WDI 2020 and authors’ calculations Note: Wanted fertility rate is an estimate of what the total fertility rate would be if all unwanted births were avoided, based on Demographic and Health Surveys (DHS). 14 2.1.2 Social norms perpetuate high fertility rates and gender inequalities Benin’s patriarchal social norms keep fertility rates high Women play an economically Women often lack the power to decide over inferior role to men their own education and sexuality Women are expected to take care of the household while The power of men over women covers most dimensions of men are seen as breadwinners and financial providers for women’s private lives, particularly education of children, their families. Women’s societal role strongly limits their health, sexuality, and family planning. physical mobility. In Benin, 75.1% of households are headed by men. Men are In 2017 56.4% of women considered it was justified for a more likely to possess assets than women. For instance, woman to ask for a condom to be used during sex if she 36.4% of men and 13.0% of women own land in Benin while knows that her husband/partner has a sexually transmitted 79.5% of men compared to 51.1% of women own a cell infection (STI), a decline since 2006 when the number was phone. 70.6%. Source: Benin Gender Assessment 2021 15 2.1.2 Social norms perpetuate high fertility rates and gender inequalities Women and family planning Women lack agency in birth decisions The share of commodities in the Family planning and the availability of contraception are an 84.5% of women do not use a family A 14 export planning method… B …but 15 …andit remains plan toabove few most use one peers in the future important determinant of fertility rates. While their use varies basket has declined over time… across countries and across the income distribution, generally policies Percentage of women not using any Women's intent to use contraceptive that facilitate gender empowerment and reproductive health also contraceptive method methods empower households and especially women to make their own 100 100% decisions regarding number of children. 87.1 84.5 80% The acceptability and use of family planning methods has 80 60% increased slowly during the last decade. The percentage of women 60 40% using a family planning method has mostly not changed in the last ten 40 years, with only 25% of women declaring that they used a 20% 35.7 24.5 contraceptive method in 2017, a choice more prevalent among 0% 20 women with many children. The unmet need for modern 2012 2018 0 contraception is estimated at 35.3% in 2020 (FP 2020). Similarly, the 2012 2017 Intend to use later Unsure Does not intend to use percentage of women intending to use family planning methods in the future has increased slowly. Openness to services exports is lower …but the time between As a result of mixed changes in social norms, women’s age at first C 16 Age at first birth has increased slightly.. D 17 Net FDI inflows remainbirths below has peers than all peers (2011-2018) remained constant birth has increased slowly though the time between births has remained constant in the past 20 years. In 2017-2018, the average age Women‘s age at first birth (in years) Months passed between previous at first birth was 19, slightly higher than a decade earlier (18.6 years in 20 child birth 2001-2002) but displaying persistent difference between rural and 40 urban areas with pregnancies happening on average almost one year 19.5 earlier in rural areas. The time between births has mostly not 35 35.6 19 changed despite the steep decline in child marriage. The number of 31.7 18.5 30 married young women aged 15-19 has been declining substantially, 27.6 18 25 from 51% in 1970 to 18% in 2020 (Appendix 5). 17.5 20 Easy access to contraceptive methods enables women to control 2001 2006 2012 2017 2001 2006 2012 2017 their fertility (Mehrotra 2016) –Box 2.2. Benin’s National Action Plan on family planning is currently being updated to revise policies, norms Total Urban Rural 15-19 20-29 30-39 and protocols in the sector, including through a better dissemination of the Law on Reproductive Health (2003). Source: EDSB-II (2001), EDSB-III (2006), EDSB-IV (2012), and EDSB-IV (2017). 16 2.1.2 Social norms perpetuate high fertility rates and gender inequalities Box 2.2 Beyond Benin: Access to contraceptives and education matters for fertility reduction. There is strong evidence that education and access to family planning are key for reducing fertility rates. In education, for example, programs subsidizing the direct or indirect cost of education can be effective in increasing enrolments and the educational performance of girls and boys, as shown in Kenya (Duflo, Dupas, and Kremer 2015). Sometimes these have a different and greater impact on women even when not gender-targeted, as in Ghana (Duflo, Dupas, and Kremer 2017). A Female Secondary School Stipend Program introduced in Bangladesh in 1994 to make secondary education free for rural girls reduced fertility by, on average, 8-12% for participating girls (Hahn et al. 2016). The study finds that the program, which covered more than two million girls each year until the 2000s, also led to an increase in age at first marriage by 0.34 years and an increase in age at first birth by 0.47 years, on average. Similarly, strong evidence supports the direct positive impact of family planning. Jones (2013) shows that a 22% reduction in the supply of contraceptives in rural Ghana due to cuts in U.S. funding led to an increase in realized fertility of, on average, 7- 10%. The study finds that most rural women were either unwilling or unable to fully offset unwanted pregnancies with traditional methods. The provision of family planning services to people who desire smaller families can both reduce fertility and increase schooling. This effect may be particularly pronounced for girls’ schooling because girls in high-fertility households are frequently kept out of school to care for their younger siblings (Canning et al. 2015). 17 2.1.2 Social norms perpetuate high fertility rates and gender inequalities Reducing gender gaps can increase GDP per capita by more than 1/10 th in 2035 2.1.3 Reducing gender gaps in The share of commodities in the Benin can have large growth per A Annual GDP growth can be 0.4 pp 18 export higher... basket has declined over time… B 19 …but it remains …Boosting above GDP levels by most 13.4%peers in 2035 capita benefits Closing gender productivity gaps and lower fertility can boost Effect on GDP growth Effect on real GDP at market prices (deviation from baseline in percentage points) (% deviation from baseline) economic growth in the short and medium term. 0.50 19.1 Policies improving human capital and labor markets will help close 20.0 the gender gap and accelerate growth. More education for women, 0.35 14.4 13.4 10.8 for example, will at the same time delay marriage age, thus reducing 4.1 6.9 5.5 5.4 total fertility, and prepare the demographic transition. Policies to 0.14 0.14 3.8 4.4 2.5 0.05 1.8 promote better labor market integration and sector’s competitiveness 0.00 0.0 in female-intensive sectors is also important. It is estimated that 2025 2030 2035 compared with females, males are 19% and 54% more productive in Closing agricultural gender productivity gap Lower fertility agriculture and service sector respectively (section 2.3). Lower fertility Closing agricultural gender productivity gap Closing gender productivity gap in services Closing gender productivity gap in services The economic benefits of reducing gender gaps (including a lower Combined scenario Combined scenario fertility rate) are estimated by applying a computable general equilibrium (CGE) model. Major scenarios considered in the model Openness Annual realto services GDP exports per capita is lower growth is … Boosting GDP per capita by 12% in include: an increase in education and health expenditures to meet the C 20 D 21 Net FDI inflows remain below peers than peers allto poised (2011-2018) increase by 1 pp… 2035 expenditure levels of aspirational peers that have lower fertility rates Effect on GDP per capita growth Effect on real GDP per capita (which in turn impacts dependency ratio and household savings); and (deviation from baseline in percentage points) (% deviation from baseline) sufficient public investment in agriculture and Active Labor Market 1.00 20.00 Policies (ALMPs) needed to close the productivity gap especially in 0.81 0.66 agriculture and service sectors (for assumption details, 11.86 9.59 Appendix 6). 0.50 6.46 1.28 3.11 4.44 The model suggests compelling results from improvement of gender 0.03 0.10 0.48 1.28 0.49 1.37 0.49 1.44 equality on growth performance. Lower fertility and reduced gender 0.00 productivity gaps in agriculture and services are associated with an 0.00 2035 additional 0.35 pp increase in average annual GDP growth and an Closing agricultural gender productivity gap Closing agricultural gender productivity gap Lower fertility Lower fertility additional 0.81 pp increase in average annual per capita growth, over Closing gender productivity gap in services Closing gender productivity gap in services the period of 2022-2035. By 2035, GDP could increase by 13.4% Combined scenario Combined scenario relative to the baseline, mostly driven by closing productivity gaps in the services sector. By then, per capita GDP will also increase 11.9% Source: Dudu and Mitik (background paper 2021. relative to the baseline, mainly as a result of a lower fertility rate. 18 2.1.2 Social norms perpetuate high fertility rates and gender inequalities Lower fertility drives employment and wage gains for female and male Lower fertility will raise labor force participation and wages for women and C Labor 22 productivity Female workers,contributed than unskilled, lessand skilled peers to per capita growth benefit from higher employment men Lower fertility is likely to increase labor force participation, EMPLOYMENT EFFECT (% DEVIATION FROM BASELINE) particularly for skilled and unskilled females; with males 2035 benefitting the most from higher wages. Closing the productivity gaps in agricultural and services has little effect on employment, as most of 3.00 2.95 2.88 2.75 2.42 2.22 the gains come from achieving lower fertility and the resulting higher 1.79 1.60 1.07 0.86 labor force participation. By 2035, the employment level of skilled 0.19 0.17 0.13 0.11 0.07 0.08 0.06 0.06 0.05 0.05 women is 2.75% higher than in the baseline while unskilled female employment increases by 2.88%. The impact on wages is also positive MALE SKILLED MALE SKILLED MALE SKILLED MALE SKILLED SKILLED SKILLED SKILLED SKILLED TOTAL TOTAL TOTAL TOTAL UNSKILLED UNSKILLED UNSKILLED UNSKILLED UNSKILLED UNSKILLED UNSKILLED UNSKILLED FEMALE FEMALE FEMALE FEMALE FEMALE FEMALE FEMALE FEMALE across all scenarios. Women are likely to earn higher wages but so do MALE MALE MALE MALE men, with skilled men benefitting the most from the higher labor participation of women. Closing the gender productivity gap increases CLOSING AGRICULTURAL LOWER FERTILITY CLOSING GENDER PRODUCTIVITY COMBINED SCENARIO wages for all categories of workers. GENDER PRODUCTIVITY GAP GAP IN SERVICES Household income increases across all scenarios due to higher employment and wages. With higher employment and wages, women are likely to increase their contribution to household income while C Labor 23 Bothproductivity men and contributed women less seethan peers a net to per capita positive gaingrowth in wages by 2035 men benefit from the higher earnings. As such, household incomes increase. There are also potentially positive effects on their bargaining EFFECT ON WAGES (% DEVIATION FROM BASELINE) power within the household. Evidence suggests women invest more on human capital of children, for example. 2035 Fully achieving the economic gains projected by the model requires 15.2 13.7 adequate resources and an institutional framework that prioritizes 9.8 9.3 9.2 7.9 -0.6 reducing gender gaps. Substantial public expenditure is needed in 1.2 1.0 0.9 0.8 0.8 0.6 0.6 0.4 0.0 various sectors including health, education, agriculture, and social protection. Mobilizing revenue (tax and non-tax) to finance these SKILLED MALE SKILLED MALE SKILLED MALE SKILLED MALE SKILLED SKILLED SKILLED SKILLED UNSKILLED UNSKILLED UNSKILLED UNSKILLED UNSKILLED UNSKILLED UNSKILLED UNSKILLED FEMALE FEMALE FEMALE FEMALE FEMALE FEMALE FEMALE FEMALE expenditures is paramount. In 2020 the institutional framework MALE MALE MALE MALE addressing gender gaps was scattered across ministries (education, health and social affairs) and there is little coordination. A centralized CLOSING AGRICULTURAL LOWER FERTILITY CLOSING GENDER PRODUCTIVITY COMBINED SCENARIO agency with adequate oversight and authority could serve as an GENDER PRODUCTIVITY GAP GAP IN SERVICES integrator and complement other initiatives such as the implementation of a gender-informed budgeting process. Source: Hasan Dudu and Lulit Mitik (background paper 2021) See Appendix 6 for more details on assumptions. 19 2.1.2 Social norms perpetuate high fertility rates and gender inequalities HEALTH AND EDUCATION SYSTEMS NEED TO ENABLE ADEQUATE HUMAN 2.2 CAPITAL ACCUMULATION The human capital stock in Benin is insufficient to promote a demographic transition. Access to education and health have improved, but quality is still low, partly due to the lack of an adequate financing strategy. Benin will need to improve quality and increase investments in health and education to meet growing demand in the future and reap the benefits of the demographic dividend. This section builds on the Human Capital Project 2020. 20 2.2.1 Low levels of human capital prevent productivity growth Benin’s next generation will be slightly less productive than its structural peers’ (except Rwanda). Its human Benin is at the lower end of the Human 24 capital level is below what is expected given its GDP Capital Index per capita. The Human Capital Index (HCI) measures the consequences of neglecting investments in human capital in terms of the lost productivity of the next generation of workers (World Development Report, WDR 2019). Its score of 0.4 in the HCI means a child born in Benin in 2020 will be 40% as productive when they grow up as they could have been if they had enjoyed complete education and full health. While generally on par with structural peers, low levels of human capital are a major constraint for Benin’s productivity growth. As innovation continues to accelerate, developing economies will need to take rapid action to ensure they can compete in the economy of the future. They will have to invest in their people, especially in health and education, which are the building blocks of human capital (Box 2.3) to harness the benefits of technology. Adjusting to the changing nature of work also requires rethinking the social contract. Investing in people also means protecting them, yet four out of five people in developing countries have never known what it means to live with social protection. People working in the informal sector are unprotected by Source: WDI, HCI, WDR 2019. Note: GDP = gross domestic product; PPP = purchasing power parity. The human capital index ranges between 0 and 1. The index is measured in terms of the productivity of the next generation of stable wage employment, social safety nets, or the benefits of workers relative to the benchmark of complete education and full health. An economy in which the average education (see Section 2.3) (WDR 2019). worker achieves both full health and full education potential will score a value of 1 on the index. 21 2.2.1 Low levels of human capital prevent productivity growth Box 2.3 The role of health and education in human capital accumulation Human capital is the stock of skills, habits, The role of education and health sectors and social attributes that enables individuals in society to perform labor (Becker 1993). The Financing education and health sectors are decisive in developing human capital. According to the human capital theory, education is an investment that prepares individuals for the labor force; it increases productivity and can thus encourage a country’s growth (Nafukho, Hairston, and Brooks EDUCATION & HEALTH 2004). Health is also a foundational investment in Access Quality a country’s human capital. Being unhealthy SECTORS reduces the ability to work productively, to learn and to further invest in human capital. Quality, access to, and financing of education and health need to be adequate so that current and especially future youth cohorts are healthy, educated, and thus productive, enabling potential demographic dividends. Human Capital Accumulation 22 2.2.1 Low levels of human capital prevent productivity growth Outcomes in education in Benin Education levels are improving; efforts need to continue C Labor 25 Halfproductivity contributed of the active populationless than has nopeers to per capita education, growth but the level of education is improving The active population is characterized by low levels of education. Half of the active population has no education. The labor force in Active population (share of respective population group) Benin is mostly young, with 61.2% of workers aged between 15-34 55.9 53.4 53.3 years and poorly educated (about 67.7% of workers have primary 52.8 50.9 50.4 49.1 47.2 46.7 46.7 43.2 education or below). 38.8 34.5 28.7 28.1 26.9 26.8 24.4 While levels are improving for the younger generations, many 17.4 15.7 children still lack proficiency in basic skills. The level of education 5.4 4.0 of the workforce improved between 2015 and 2018, with the share of workforce with no education declining by 5pp, while the share with primary, secondary and post-secondary education increased Post secon Female No education Secondary 1 Male 15-24 25-34 35-64 Primary Urban Rural significantly. Yet, many children lack proficiency in basic skills. In 2019, while language and math skills improved throughout primary 2015 2018 education, there were significant disparities. On the positive side, Benin outperforms peers in language skills improvements throughout Sex Area Age Education the period of primary education. The trend on math skills is less C In 2019, students in primary school performing wereto at par with (and better than some) 26 Labor productivity contributed structural peers less than peers per capita growth satisfactory, despite Benin‘s performance being comparable to that of structural peers Togo and Senegal. Language skills of primary school students in 2019 Math skills of primary school students in 2019 Benin Togo Senegal Benin Togo Senegal Significant effort is being directed towards improving education 100% 100% as per the Sectoral Plan on Education (2018-2030) but these efforts 90% 90% 80% 38 24 19 80% 37 need to continue. This plan is built around four priorities: (i) 47 70% 48 70% 62 52 65 establishing a twelve-year universal basic education; (ii) developing a 60% 75 75 60% 79 vocational training system adapted to the needs of the private sector; 50% 50% 40% 40% (iii) improving the quality of teaching and learning; and (iv) developing 76 61 30% 62 52 30% 53 63 more effective, efficient and inclusive governance. Tangible progress 48 20% 25 25 20% 38 35 has been made in increasing access to basic education. However, 10% 10% 21 0% 0% there are persistent and considerable geographic and social Beginning End Beginning End Beginning End Beginning End Beginning End Beginning End disparities in the provision and quality of primary education services; Below threshold Above threshold Below threshold Above threshold and gender gaps persist across the different levels although they are Source: EHCVM 2018 more marked at secondary school level (see earlier section). Note: charts A and B show the share of students reaching a threshold in skills at the start and at the end of primary school . See more: the Human Capital Project 2020 23 2.2.1 Low levels of human capital prevent productivity growth Additional focus needs to be put on improving health outcomes Benin performs worse than most structural peers on basic health 27 While health outcomes have improved in the indicators past decade, large gaps remain Indicator Benin Rwanda Senegal Togo Benin still faces large challenges in the health sector. Life expectancy at birth, 2019 61.5 years 69 68 61 Infant and maternal mortality rates, though decreasing slowly, remain high, well above the average for low and lower-middle Maternal mortality rate, 2017 397/100 000 live births 248 315 396 income countries (2018). Malaria continues to be the leading cause of medical consultation (44.3% of cases), hospitalization Under-five mortality rate, 2019 64/1000 live births 29 36 50 (29.9%), and mortality (36.7%) among children under five. The Neonatal (<1 month) mortality rate, 2019 30/1000 live births 16 22 25 current levels of stunting have slowly come down from a high of 45% in 2006 to 32% in 2018 but remain high compared with Children <6 months exclusively breastfed, 2019 42% 87% 42%* 57%* other West African countries and pose considerable risk of delayed socio-economic growth (National Health yearbook Children 12-23 months DPT immunized, 2019 76% 98% 93% 84% 2019; Demographic and Health Survey 2018-2019). Children <5 years who are stunted, 2018 32% 33% 18% 24% The need to invest in health systems to ensure the productive capabilities of the population has been recognized and Pregnant women receiving prenatal care, 2018 83% 98% 98% 78% incorporated in the sectoral plan and the development of the Skilled attendance at delivery, 2018 78% 91%* 75% 69% health insurance program ARCH. The challenge of overcoming a legacy of limited investment in human capital and social Incidence of malaria, 2018 386/1,000 population at risk 487 56 267 resilience systems remains large. Incidence of tuberculosis, 2019 55 57 117 37 Source: WDI, IGME UN Inter agency Group for Child Mortality estimation, and authors’ calculation. Notes: * latest data is for 2015. 24 2.2.1 Low levels of human capital prevent productivity growth Quality of health and education remains low 2.2.2 While access to health and The share of commodities in the education has improved, quality 28 export A Access to education has improved… basket has declined over time… B 29 …but it …but remains quality above needs most a further peers boost remains low Primary and secondary school Trained teachers in primary education Access to education has increased but quality still needs a boost. enrolment (% gross) (% of total teachers) Since the 2000s, Benin has achieved full schooling at the primary 200 level. In 2000, 82.5% of children went to primary school compared 100 71 with 122% in 2018 (gross). Enrolment in secondary schools also 100 47 increased from 21.8% in 2000 to 59% in 2016, but significant gender 50 disparities persist. Yet, while access has risen, the quality of education 0 is still low, hindering the adequate formation of the next generation of 0 workers. Teachers’ education has been improving but it is still poorer 2010 2019 2010 2019 2011 2019 than for structural peers, and while student-teacher ratios have been Primary Secondary Benin Senegal Togo Rwanda Benin Senegal Togo Rwanda declining, they remain slightly above peers at 40.9 in 2019. Progress in the health sector has been slow, despite increasing Source: WDI and authors’ calculations; Source: WDI and authors’ calculations investments due to COVID-19. At national level, access to primary health care services meets WHO standards, but there are regional Openness to services Access to healthcare exports has is lower been slower to C 30 D 31 Net FDI …and inflows quality remain remains below peers insufficient disparities. The quality of healthcare services is inadequate, and the than all peers (2011-2018) improve… quality of hospitals has not improved over the period 2015-2018. In 90 Percent of hospitals sufficiently and 2015, 5% of hospitals in Benin were sufficiently equipped, compared 80 insufficiently equipped to only 3% in 2018. Only 64% of hospitals were basically equipped in 70 2015, while 63% had basic equipment in 2018. There have been 80% 64% 63% significant investment in 2020 in response to the COVID-19 crisis with 60 60% improvements in emergency response and lab capacity, but gaps 40% 50 remain large. 2001 2006 2012 2014 2018 20% 5% 3% 0% Births attended by skilled health staff (% of total) Sufficient equipment Basic equipment Immunization, DPT (% of children ages 12-23 months) 2015 2018 Source: SARA-2015, SARA-2018. Source: SARA-2015, SARA-2018. 25 2.2.2 While access to health and education has improved, quality remains low 2.2.3 Human capital investment is insufficient Human capital is underfinanced, particularly the Government expenditure on education health sector. Indeed, Benin’s health system remains 32 (2011-2019) inadequately financed and far from meeting the Abuja % of total budget % of GDP, right axis Declaration commitment of allocating 15% of the 30.0 6.0 general budget to the health sector. Public expenditure 25.0 5.0 on health as a share of GDP is extremely low (<1%, or 20.0 4.0 4.2% of total expenditure) reflecting Benin’s limited 15.0 3.0 10.0 2.0 revenue mobilization, which constrains spending 5.0 1.0 capacity. 0.0 0.0 Benin Lanka Rwanda Togo Senegal Ghana As a result, households’ contributions to covering health Sri expenditures have increased, as has dependency on extra-budgetary spending. Education has been much Government expenditure on health better funded, representing about 20% of the total 33 (2011-2019) budget over the same period. However, spending remains extremely low when measured as a share of % of total budget % of GDP, right axis GDP (3.3%) and has been declining. A recent analysis 10.0 2.5 has however found that public spending efficiency is 8.0 2.0 relatively adequate in the two sectors (IMF 2020). 6.0 1.5 Countries that have managed to achieve a sustained 4.0 1.0 2.0 0.5 growth acceleration have invested in human capital. A 0.0 0.0 successful example is South Korea during the late Benin Togo Rwanda Senegal Ghana Morocco Sri Lanka 1960s-1980s (See more – South Korea’s experience, Appendix 8). Source: WDI, IMF and author‘s calculations. 26 2.2.3 Human capital investment is insufficient IMPROVING THE QUALITY OF THE LABOR MARKET IS PARAMOUNT 2.3 TO ABSORB YOUTH AND WOMEN Although unemployment is low, the labor market does not generate enough good jobs. Women and youth face many hurdles. If the working age population continues to grow, Benin’s labor market will face increasing pressure. Benin needs to create better jobs that match workers’ skillsets and that are productivity-enhancing. The inability to achieve this would mean a loss of human and economic potential for the country. 27 Figure 16. Labor market participation is high 2.3.1 Labor market participation is high, and unemployment is low… Benin’s low unemployment rate is consistent 34 Labor force participation is above peers 35 with the large informal sector Most of the working age population in Benin is active in the labor market. Labor market participation is higher in Benin than in Labor force participation rate, total (% of total Unemployment, total (% of total labor force) most of its structural and aspirational peers. In 2019, almost 72% of population ages 15-64) 2000 2010 2020 the working age population participated in the labor market: 70% of 2000 2010 2019 women against 73% of men. The participation rate has been constant 100.0 14.0 12.0 10.1 over the last two decades. 84.1 71.7 69.2 10.0 80.0 58.5 48.7 57.5 8.0 7.1 The unemployment rate is low, which is common in many 60.0 47.1 40.0 6.0 4.1 4.8 4.5 countries in the region. Overall, while unemployment has increased 4.0 2.5 20.0 2.0 1.4 in the past two decades, it remains marginal at 2.5% of the total 0.0 0.0 working age population in 2020. It mostly concerns post-secondary Benin Togo Senegal Rwanda Ghana Morocco Sri Lanka Benin Togo Senegal Rwanda Morocco Sri Lanka Ghana Structural peers Aspirational peers Structural peers Aspirational peers educated individuals, and higher income quintiles. Higher unemployment among these group suggests a large prevalence of Source: World Development Indicators 2020. Source: World Development Indicators 2020. underemployment and self-employment that explains the high employment levels. Benin has indeed a very large informal economy. 36 Labor productivity Unemployment contributed rates are lessare low, and women than peers worse to per capita growth affected Women, however, display higher unemployment at all levels of education and welfare quintiles. Unemployment rates by education and welfare quintiles Of its structural peers, Benin’s labor market is most similar to Post-secondary Rwanda’s, with both displaying characteristics associated with widespread informality. In 2011, only 7% of employment was in the Education Secondary Primary formal wage sector in Rwanda, with low earnings and No education Total underemployment. Low earnings reflected in large part the unskilled Q5 Female nature of the labor force, employed mostly in agriculture Quintiles of Q4 (concentrated in cocoa) or low-skill services. welfare Male Q3 Q2 Q1 0.0 2.0 4.0 6.0 8.0 10.0 12.0 Source: EHCVM, 2018. 28 2.3.1 Labor market participation is high, and unemployment is low… …But most jobs are in the informal sector, and mainly self-employment Formal jobs account for less than 10% of Almost 90% of informal businesses do not have 37 38 employment employees As in many LICs, both women and men are predominantly The opportunity for wage work in the informal sector is extremely employed in the informal sector, although the proportion of women limited. Around 90% of Benin’s production units in the informal sector is higher. Similarly, the informal sector is more important in rural areas only consist of the business owner, implying self employment. Only than in urban areas, and the share of young people aged 15 to 24 who 5.3% have two employees (the owner plus a wage worker), with a higher work in the informal sector is greater than that of older people. In proportion of male owners in this category. The prevalence of informal comparison, the formal sector is more important in urban areas and the employment creates significant vulnerability for workers in times of proportion of men in the formal sector is higher. shocks, as they are not covered by safety nets. The COVID-19 crisis (Box 2.4) has had short-term impacts on most self-employed. Employed Public employment Full time Formal status of jobs No Yes No Yes Informal Formal One staff 2 staff 3 staff and + Female 56 99 1.0 78.1 21.9 95.5 4.5 91.5 89.9 89.6 91.1 88.8 89.8 86.3 Sex Male 68.5 96.1 3.9 77 23 86 14 Rural 61.3 98.9 1.1 83.5 16.5 94.5 5.5 Areas Urban 63.2 96.3 3.7 71.7 28.3 86.9 13.1 15-24 30.4 99.5 0.5 74.3 25.7 94.8 5.2 Ages 25-49 79.2 96.3 3.7 77.3 22.7 86.5 13.5 50-64 79.4 97.1 2.9 80.8 19.2 91.5 8.5 Female Male Rural Urban 15-34 35-64 Total 62.5 97.6 2.4 77.6 22.4 90.7 9.3 Sex Areas Ages Total Source: EHCVM, 2018. Source: ERI ESI 2018 Note: The chart displays the distribution of employment per sector as percentages. Note: The chart displays the number of workers in informal sector enterprises as percentages. 29 2.3.1 Labor market participation is high, and unemployment is low… Box 2.4 The impact of COVID-19 on the labor market In Benin, COVID-19 cases and deaths have remained low. As a result, and supported by a rapid and large countercyclical fiscal response, the COVID-19 B2 Impact of COVID-19 on hours worked and income crisis has had only a moderate impact on Benin’s short-term growth, with Round 1 (June-July 2020) Round 2 (November-December 2020) most of the contraction in the second quarter (see Chapter I). Still, the medium-term impact of temporary job losses could have more long-lasting 90.5 77.0 effects. A high frequency survey conducted by the World Bank (WB) and the 64.6 55.1 44.9 National Statistics Institute (INSAE) in June and November 2020 reveals that: 23.0 35.4 9.5 • 23% of the working-age population surveyed in June 2020 were not working, among which 2/3 had been working before the onset of the Total But working before the But, not working before the pandemic in March 2020. beginning COVID-19 beginning COVID-19 pandemic pandemic • Six months later, only 9.5% of the population surveyed was not working, of Worked at least 1h in the Did not work at least 1h in the past week which half had been working before COVID 19. past week • 52% of people surveyed in June and 26.8% surveyed in November 2020 89.3 declared working fewer hours than before the pandemic. 56.6 • With respect to income, 89.3% of the people surveyed in June 2020 declared having lost their income since the beginning of the pandemic, but 32.8 in November 2020 the figure was only 8.7%. 8.7 10.7 0 0 2.0 • However, while only 10.7% declared a reduction in income in June 2020, Lost all income from your Earned income but less than Earned about the same Earned more income than 56.6% declared a reduction in income six months later. work (income decreased to usual (decreased income) income as usual (income usual (increased income) 100%) unchanged) Source: ETHF-Covid-19/INSAE/ World Bank, 2020 30 2.3.1 Labor market participation is high, and unemployment is low… Low wages are predominant Wages and incomes are generally low, except for skilled wage jobs A 39 it remains above most peers …butCFA/year) Most workers earn less than the minimum wage (480,000 Widespread informality is reflected in generally low wages. Most self-employed, family workers, apprentices, and household aides – Yearly wage per work category (in %) representing 88.7% of the working age population - earn less than the Self employed 45.2 29.0 20.1 5.7 minimum wage (480,000 CFAF/year). In addition, 49% of unskilled Family worker 45.8 43.2 0.0 11.0 employees earn the minimum wage or below. Further, wages are Paid trainee or apprentice 30.9 32.8 34.8 1.4 concentrated around the minimum wage regardless of hours worked, Laborer, household help 35.0 41.3 21.8 1.8 especially for young people and women, reflecting poor quality jobs. Unskilled worker or employee 18.6 30.5 42.4 8.5 Skilled worker or employee 3.5 12.3 54.7 29.5 Low earnings reflect underemployment, and the unskilled Middle manager / supervisor 1.6 6.4 23.0 69.0 nature of the labor force. While younger workers are being better Senior manager 0.8 0.0 12.4 86.8 educated, 50% of the labor force did not complete primary education. < 250.000 [250.000-480000[ [480000-1.000.000[ >=1.000.000 Indeed, there is a clear divide with formal or higher skill jobs. Individuals with jobs requiring better education earn substantially Source: EHCVM 2018 ; Note: The chart displays the proportion of employment and wage per work category as percentages. more. Only 16% of skilled employers and about 8% of supervisors report yearly salaries that are below the minimum wage. This is C Openness The minimumto services exports is lower wage predominates D Labor Net FDIproductivity has grown inflows remain more below peers consistent with the existence of higher returns to education in the 40 than all peers regardless (2011-2018) of hours worked 41 slowly than in peer countries formal sector (see Chapter I). 40000 GDP per person employed Low labor productivity also likely explains the low wage levels. 30000 (constant 2017 PPP $) Benin’s worker productivity increased by one third from the early 20000 2000s to 2019. Yet, the increase was slower than for most peers (except Togo) and it remains four times lower than in Sri Lanka and 10000 three times lower than Morocco. While employment has grown out of 0 agriculture consistently in the past decade, the services sector has Benin Togo Senegal Rwanda Ghana Morocco Sri Lanka failed to create higher quality jobs, with most jobs in retail, commerce and hospitality. Reaping the benefits of the demographic dividend Structural peers Aspirational will mean creating of better-quality wage jobs. A first good job allows peers young workers to learn new skills and non-cognitive aspects of a job. 1999 2005 2010 2015 2019 For the economy, good jobs mean higher overall productivity of the Source: EHCVM 2018 and authors’ calculations Source: WDI, and authors’ calculations labor force, and thus higher growth and welfare. 31 2.3.1 Labor market participation is high, and unemployment is low… Agriculture and services are the biggest employers, with women predominantly employed in the tertiary sector Most employment is in services and Services have higher labor productivity, 42 43 Most men work in agriculture, while women agriculture but it has stagnated in the last 20 years work predominantly in services. Overall, both sectors account for about 80% of total Decomposition of employment by sector Labor productivity per sector (constant in 2020 (% of total employment) local currency unit) employment 2,500.0 Ghana 28.5 22.2 49.4 Aspirational peers The primary sector remains one of the main employers, Sri Lanka 23.7 30.4 45.9 2,000.0 especially for men, with 45% of men and only 30% of women Morocco 34.1 21.8 44.0 active in the agriculture sector. Most women are employed in 1,500.0 services (54%). Benin has the second largest share of Rwanda 61.7 9.1 29.2 Structural employment in agriculture among its peers, which reflects the Peers Senegal 29.4 13.6 56.9 fact that agriculture still accounts for almost 27% of GDP 1,000.0 Togo 37.2 12.9 49.9 (2019, WDI), the highest among all peers, followed by Rwanda (24%) and Togo (23%). Total 38.0 19.1 42.9 500.0 Benin The country has still to undergo a structural transformation of Male 46.1 21.6 32.3 its economy, despite employment shifting away from Female 29.6 16.5 53.9 agriculture in the past decade. Labor productivity has - increased slowly, reflecting its stagnation in the services 0.0 20.0 40.0 60.0 80.0 100.0 2000 2005 2010 2015 2016 2017 2018 sectors where employment has grown the most (see Chapter I). This partly reflects that services jobs are mostly in retail and Employment in agriculture Employment in industry Primary (Agriculture) Secondary (Industry) non-tradable services. Employment in services Tertiary (Services) Global (All three) See more: Appendix 7 on agricultural employment Source: World Development Indicators 2020, ILO projections Source: World Development Indicators 2020. Note: Emplyment rate per sector as%age of total employment. 32 2.3.1 Labor market participation is high, and unemployment is low… Women and youth work profiles 2.3.2 Women and youth face higher The share of commodities in the entry barriers into labor markets itpeople Young generally areabove more A 44 export Women are twice as inactive as men B 45 …but remains inactive most peers Entering the labor force is more difficult for women and youth basket has declined over time… than it is for adult men: 13.4% of working-age women are inactive Working and schooling profile within the Working and schooling profile within the working age population (not working and not in school) compared to only 6.6% of working-age working population per age & per sex 100% 100% men. The inactivity gender gap declines with age, suggesting it is 80% linked with reproductive age for females, and that it fades with time 60% for men. From 25 years old up to 55, inactivity in the male working 40% 76.2 76.4 76.3 age population is very limited. 20% Youth move into self-employment as they get older. Youth leave 0% 0% Male Female 15-2425-3435-4445-5455-6415-2425-3435-4445-5455-64 unpaid positions to go into more productive jobs gradually from 20 to Sex All 30 years old, mostly leaving trainee or apprenticeship positions and Male Female Not working & in school Not working & Not in school Not working & in school Not working & Not in school unpaid family business for self-employment. As in many other Working & in school Working & not in school Working & in school Working & not in school developing economies, most workers are self-employed because they Source: EHCVM 2018-2019 Source: EHCVM 2018-2019 have no choice. In fact, most age groups and genders report similar strategies when looking for jobs – with most of the population using Openness to services exports is lower Most people find jobs through personal personal relationships followed by self-reliance, particularly in C 46 Age affects job(2011-2018) categories D 47 Net FDI inflows remain below peers than all peers contacts creating their own business. The pattern of employment by age suggests young people who fail to find adequate wage jobs in the first Work category per age group (in %) Business owner Ways to find employment in % years of active life move later into self-employment as a second-best 100.0 Self employed Personal Relationships,… option. 90.0 80.0 Personal approach (create… This points to two possible strategies to support better job creation Family worker 70.0 contributing to a family Announcement from Radio,… and labor productivity growth: (1) improving earning opportunities by 60.0 business Unpaid trainee or competitive recruitment… 35-64 supporting the formal private sector, and actively supporting the 50.0 40.0 apprentice 15-34 workforce through training and search options (notably, youth mostly ANPE 30.0 Paid Trainee or Total rely on the jobs agency Agence Nationale pour l’Emploi – ANPE, for their Apprentice 20.0 Other search); and (2) improving the returns to labor of the self-employed Laborer, housekeeper 10.0 Placement firm with similar but sector-focused policies (Fields 2019, Box 2.6). 0.0 Unskilled worker or 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 0 20 40 60 80 employee Source: EHCVM 2018-2019 Source: EHCVM 2018-2019 33 2.3.2 Women and youth face higher entry barriers into labor markets Young people and women are more likely to be underemployed More than 90% of rural women and people under 25 are In 2015, 72% of the active population was 48 underemployed underemployed – mostly young and rural women. Characteristic of underemployment Sex and living area Total 28.0 10.0 37.0 25.0 In Benin, the phenomenon of underemployment is most Males-urban 49.0 13.0 24.0 14.0 severe when viewed through the lens of earnings, as Males-rural 31.0 14.0 32.0 23.0 individuals earn less than the minimum wage (SMIG), which is Femmes-urban 22.0 6.0 45.0 27.0 approximately equivalent to the poverty line. Females-rural 9.0 6.0 47.0 39.0 The percentage of employed individuals earning less than the No education 19.0 9.0 41.0 30.0 minimum wage decreases with age: youth (15-34 years) are Primary 19.0 9.0 41.0 30.0 Education much more likely to earn less than the minimum wage than Secondary 1 41.0 10.0 31.0 19.0 older individuals. Secondary 2 56.0 17.0 15.0 13.0 Post secondary 63.0 26.0 4.0 7.0 It also decreases as the level of education increases: 81% of 15-24 8.0 4.0 52.0 36.0 Benin’s labor force with no education or only primary education is underemployed, compared to only 37% of those 25-34 27.0 11.0 36.0 27.0 Age with post-secondary education. 35-54 35.0 11.0 33.0 21.0 55-64 27.0 12.0 34.0 28.0 Women are over twice more likely to be underemployed and are much more vulnerable to underemployment in rural areas, compared with men. No underemployment Employment<35 hours Employment