Research & Policy Briefs From the World Bank Malaysia Hub No. 39 October 27, 2020 Exploring the Potential of Gender Parity to Promote Economic Growth Sharmila Devadas and Young Eun Kim Narrowing the gender gap is critical to sustainable and inclusive growth. This brief discusses how moving toward gender equality can improve female labor force participation, human capital, and total factor productivity, leading to higher economic growth. The analysis simulates the cross-country impact of increasing female labor force participation and education on GDP growth for the next three decades. In practice, achieving substantial gains in gender equality across generations will require sustained efforts to reset gender norms, starting with the young, and to increase women’s economic participation and voice in society in areas of influence. A Persistent Shortfall in businesses, and many fathers are taking a greater responsibility for housework and childcare. Gender equality is a Gender equality will not happen in this generation or the next. key agenda for many countries and multilateral development If recent trends continue, it will take more than 99 years to institutions, not only because it is an end in itself, but also in achieve full gender parity globally, the World Economic Forum recognition of its centrality to reducing poverty and achieving (WEF) estimates (WEF 2019). WEF’s measure of the global sustainable and inclusive growth (UN 2015; World Bank 2015). gender gap shows that the biggest shortfall is found in political empowerment, followed by economic participation and This brief explores gender disparity across income groups opportunity. The COVID-19 pandemic has hit women around and regions, referring especially to indicators of human capital the globe especially hard (ILO 2020). The economic recessions and economic participation and opportunity. It discusses how triggered by the pandemic, especially in sectors with a high greater equality can improve key growth drivers according to a share of female employment, and lockdown measures including standard Solow-Swan type model and lead to higher economic closings of schools and daycare centers have hurt women’s growth. It then reports on simulations of the growth potential employment and wages, while increasing their domestic labor across countries from increasing women’s labor force and caretaking duties at home (Madgavkar et al. 2020, The New participation and educational attainment, as measured using York Times 2020). The unprecedented pandemic, however, may the World Bank Long-Term Growth Model (LTGM) toolkit. The lead to a positive change toward gender equality (Alon et al. brief concludes with policy recommendations to increase 2020). Flexible working arrangements are being adopted gender parity. Figure 1. Female Human Capital Indicators by Income and Region Women’s health and educational attainment are as good as or better than men’s. A. Health B. Educational Attainment AII HI UMI LMI LI EAP ECA LAC MENA SA SSA 0 25 50 75 100 0 2 4 6 8 0 10 20 30 40 -6 -4 -2 0 2 4 6 Women’s life Difference versus Share of women Difference versus expectancy at birth men (years) (≥25 years) with some men (pp) (years) tertiary education (%) Source: Authors' calculations based on United Nations Population Division data in World Development Indicators, ILOSTAT data, and World Bank country income group classifications. Note: Health indicators are median values for 2017. Educational attainment indicators are median values of 2014–18 averages. The sample comprises 136 countries. Income is categorized by high income (HI), upper-middle-income (UMI), lower-middle-income (LMI), and low-income (LI). Region is categorized by East Asia and Pacific (EAP), Europe and Central Asia (ECA), Latin America and the Caribbean (LAC), Middle East and North Africa (MENA), South Asia (SA), and Sub-Saharan Africa (SSA). Pp is percentage points. Affiliations: Sharmila Devadas, Central Bank of Malaysia; Young Eun Kim, East Asia and Pacific Chief Economist Research Center, World Bank. This brief was written while Sharmila Devadas was on secondment to the World Bank. Acknowledgements: The authors thank Norman V. Loayza, Elizaveta Perova, Achim D. Schmillen, and Nurlina Shaharuddin for valuable comments and suggestions. Nancy Morrison provided excellent editorial assistance. Objective and disclaimer: Research & Policy Briefs synthesize existing research and data to shed light on a useful and interesting question for policy debate. Research & Policy Briefs carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions are entirely those of the authors. They do not necessarily represent the views of the World Bank Group, its Executive Directors, or the governments they represent. Exploring the Potential of Gender Parity to Promote Economic Growth Figure 2. Female Labor Force Participation Rate (LFPR) by Income and Region Women trail men in their participation in the labor force. 80 0 -10 60 -20 -30 40 -40 -50 20 -60 0 -70 All HI UMI LMI LI EAP ECA LAC MENA SA SSA Female LFPR in 1990 (%) Female LFPR in 2018 (%) Female versus male LFPR in 1990 (pp), RHS Female versus male LFPR in 2018 (pp), RHS Source: Authors' calculations based on ILOSTAT data in World Development Indicators and World Bank country income group classifications. Note: Female (male) participation rates are for female (male) populations ages 15–64. All values are medians. The sample comprises 136 countries, as in figure 1. See notes to figure 1 for explanation of the income and region acronyms. RHS = Axis on the right hand side. What Are the Characteristics of Gender Inequality Europe and Latin America; similar in East Asia and Middle East; around the World? and lower in South Asia and Sub-Saharan Africa. Human capital is enhanced by a healthy and educated Despite human capital outcomes that are as good as or population. Globally, women appear to be healthier than men. better than men’s, women trail behind in labor force Across income groups and regions, women’s life expectancy at participation—although participation rates have increased over birth exceeds that of men (figure 1A). Women’s educational time and the gender gap has narrowed (figure 2). Generally, attainment is as high as men overall, but varies more than female participation rates follow a U-shaped pattern, falling as health across income groups and regions (figure 1B). Women countries transition from agricultural to industrial economies are more likely to receive at least some tertiary education as and then rising in more modern economies as education levels compared to men in high-income and upper-middle-income rise, fertility rates fall, and gender norms evolve (Goldin 1995, countries, and less in lower-middle-income and low-income 2006). Regionally, female labor participation rates are countries. At the regional level, the share of women with at especially low in countries in the Middle East and North Africa least some tertiary education as compared to men is higher in (MENA) compared to countries with similar income levels in Figure 3. The Quality of Female Employment by Income and Region Gender segregation by occupation occurs across income groups and regions. A. Employment Status B. Occupation All HI UMI LMI LI EAP ECA LAC MENA SA SSA All HI UMI LMI LI EAP ECA LAC MENA SA SSA 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 Female share (%) of: Contributing family workers Female share (%) of: Managers, professionals and technicians Employers Clerical, service and sales workers Own account workers Craft and trade workers, operators and assemblers Wage employees Elementary and skilled agriculture workers Total employment Total employment Workers with advanced education Source: Authors' calculations based on ILOSTAT data and World Bank income group classification. Note: Self-employment comprises employers, own account workers and contributing family workers. All values are medians of 2014-2018 averages. The sample comprises 119 countries, a subset of the countries featured in Figures 1 and 2. See notes to Figure 1 for explanation of the income and region acronyms. 2 Research & Policy Brief No.39 other regions (figure 2). This is partly attributable to women Women and Effective Labor marrying younger and exiting the labor force upon marriage, as well as a relatively smaller expansion in the services and Reforms undertaken now to increase the human capital of manufacturing sectors that are more likely to employ women girls—through reduced stunting and longer and better-quality (Verme 2015). schooling for more girls—will not have an immediate effect on growth, but will yield results gradually over time as young Women who participate in the labor force are women join the workforce. Meanwhile, for a given level of overrepresented as unpaid workers mostly working in human capital, a rise in female labor force participation that family businesses (contributing family workers) and starts now will lead to higher economic growth immediately underrepresented as employers. This pattern is observed and over the long term. The gap between female and male across income groups, despite the high share of female workers labor force participation rates is associated with average with advanced education in high-income and upper-middle-income long-term per capita income losses of about 9 percent in groups (figure 3A). As a country transitions to a higher income Organisation for Economic Co-operation and Development level, the share of self-employed women without hired (OECD) countries and up to 30 percent in MENA countries, employees (own-account workers) decreases and the share in Cuberes and Teignier (2016) find, using an occupational choice total wage employment increases (figure 3A). In low-income model. countries where women with advanced education make up a smaller share of the workforce, women’s share of wage In countries whose population is aging, an increase in employees is nearly half that of vulnerable employment such female labor force participation can help partially offset the as family workers and own-account workers. By contrast, the decline in labor supply caused by a shrinking share of the female share of wage employees is almost the same as the working-age population. For instance, an increase in Japan’s share of vulnerable employment in middle-income countries, labor force due to female, elderly, and immigrant entrants has and 1.3 times higher in high-income countries. contributed to the country’s economic expansion in recent years, Ip (2019) finds. In a simulation for East Asian countries, Gender segregation by occupation exists across all income Özden and Testaverde (2014) show that an increase in female groups and regions. Women are overrepresented in clerical, participation would mitigate the decline in the total labor force, sales, and service roles—traditionally thought of as women’s followed by an increase in labor participation of migrants and work—and underrepresented in similarly medium-skilled craft the elderly. Countries in the early stages of demographic and trade work, plant and machinery operation, and assembly transition, meanwhile, can reap the benefits of their demographic (figure 3B). In terms of high-skilled jobs (managers, professionals, dividend period (where the share of the working-age and technicians), the proportion held by women is almost the population expands more than that of dependents) by same as their level of educational attainment, as reflected by facilitating adult women’s participation in the labor force now their share of workers with advanced education. Various and increasing the human capital of girls to maximize the size of studies in different regions and income levels show that the effective labor force in the future. occupational sorting contributes to the gender wage gap more than differences in education levels, including for 11 African With more women working, some have argued that fertility countries (Fafchamps, Soderborn, and Benhassine 2008), rates can drop to less than desirable levels. But it is hard to Vietnam (Chowdhury et al. 2018), and the United States (Blau generalize a causal effect across countries, subpopulations, and and Kahn 2017). time periods (see Kim 2016, for instance, regarding the causal effect of women’s education on fertility). Matysiak and Vignoli How Does Reducing Gender Inequality Improve (2008) show that there is a negative but weakening impact of Economic Growth? female employment on childbearing over time, and a negative but strengthening influence of young children on women’s Based on the Solow-Swan growth model, the determinants of employment for the majority of Western industrialized economic growth comprise effective labor, physical capital, and economies. Importantly, they find that these effects vary across total factor productivity (TFP). The growth in effective labor is country contexts, depending on the opportunity costs in a driven by human capital per worker and the number of workers given country, which revolve around institutional support, labor (the working-age population that participates in the labor market conditions, and gender norms. In fact, at the force). Population growth is a drag on per capita GDP growth cross-country level among advanced economies, there has because it dilutes resources—unless the number of been a shift from negative to positive correlation between working-age men and women grows faster than dependents fertility and female labor force participation in the last three (young children and the elderly). The effect of investment in to four decades, pointing to the importance of these physical capital on economic growth diminishes quickly as between-country differences. In the United States, while in the physical capital accumulates—unless the accumulation is 1990s highly educated women had fewer children than women accompanied by other reforms to boost effective labor and TFP. with a lower education, this is no longer true. The relationship TFP is the residual after considering the direct effects of between fertility and women’s education is U-shaped, as highly effective labor and physical capital. TFP is driven by how educated women now have more children, substituting a effectively and efficiently those two inputs are used to produce significant part of their parenting with childcare. Much of this total output. Among these three determinants, gender new pattern is explained by the change in the relative costs of inequality is particularly related to effective labor and TFP as childcare–becoming more affordable for women with college follows. or advanced degrees (Hazan and Zoabi 2015). 3 Recovery from the Pandemic Crisis: Balancing Short-Term and Long-Term Concerns Women and Productivity these are the key areas of gender disparity, as discussed above. These two components are related. The allocation of Total factor productivity is determined by five interrelated employment is also partly tied to women’s educational components—education, innovation, market efficiency, attainment. The simulations estimated the loss of GDP per infrastructure, and institutions—Kim and Loayza (2019) show. capita from gender gaps in labor force participation and Providing good-quality schooling to girls and thereby narrowing education for the next three decades (the 2020–50 period). the gender gap in education, especially in low-income and The LTGM toolkit (Loayza and Pennings 2018), which is built on lower-middle-income countries, would lead to a faster growth the Solow-Swan growth model, as well as the LTGM-TFP of TFP when better educated young women join the labor extension were used. market. The more educated the labor force is, the more capable it is of adapting and implementing technology from the Two scenarios were compared to assess the economic loss frontier, as well as of innovating and creating new knowledge from the gender gaps. One is the baseline in which the current (Barro 2001; Hanushek and Woessmann 2015; Khazanah gender gaps in years of schooling (2020) and labor force Research Institute 2018; Kim, Loayza, and Meza-Cuadra 2016.) participation rate (2019) remain the same for the entire period. Lower gender inequality can also enhance market efficiency In another scenario, there is no gender gap in the two with the more effective allocation of working women, for parameters for the same period. Other input parameters in the instance, in wage employment in the non-agriculture sector LTGM were assumed to remain at the current level (2019). For and as entrepreneurs (employers/self-employed persons). the direct impact of gender gaps on GDP per capita, the LTGM Gender gaps in entrepreneurship cause an average long-term was used. For the indirect impact through TFP, the study used loss in per capita income of 6 percent in OECD countries, and the LTGM-TFP, in which the TFP growth rate is a function of the between 5 and 10 percent across regions, Cuberes and Teigner TFP determinant index and the initial TFP level. To estimate the (2016) find. Ostry et al. (2018) find that women and men are change in the TFP determinant index from removing gender complements in the production process. Within the gains to gaps, the study ran a cross-sectional regression across 91 GDP they estimate is realized by closing the gender gap for developing and developed countries, in which the TFP countries with larger-than-median gaps, about four-fifths of the determinant index was regressed on the gender gap in labor increase comes from adding women to the workforce, with the force participation and human capital index (based on years of remainder due to the effect of gender diversity on productivity. schooling). Simulation of the Economic Loss from Gender Gaps in Figure 4 shows that the economic loss as the proportional Effective Labor difference between the simulated GDP per capita for 2050 of the two scenarios. Panel A shows that the average loss in This study zeroes in on the main components of effective GDP per capita due to gender gaps is the biggest for labor—education and labor force participation—given that lower-middle-income countries, followed by upper-middle-income, Figure 4. The Loss in GDP per capita from Gender Gaps in Education and Labor Force Participation, 2020–50 The average loss is greatest for lower-middle-income countries and countries in the Middle East and North Africa and South Asia. A. Average loss by income group B. Country-specific loss Total GDP per capita loss from gender gaps, percent Total GDP per capita loss from gender gaps, percent 45 25 MAR JOR 40 SDN IND EGY 20 35 TUN MRT 30 IRN 9.2 LKA TUR 15 25 GTM SEN HND 0.9 20 NER TJK KGZ NIC C RI X 10 5.1 ME 15 TGO BOL IDN DOM PRY MYS P HL ARM PAN KOR 0.1 ECU COL ARG CHL 3.5 11.2 2.3 10 CAF BEN CMR BRA ITA 5 MO ZA TZ LSO MNG C ZAFH N SR B POL H UN CZE HJ KG PN 7.1 0.1 SLE KEN UKR JAM T PEHA R RUS BGR URY HRV GRC AUSA UT SGP IRL 3.0 5 ZWE MDA NAM BWA KAZ ES BEL DE PGBR NZL FRA C AUS AUN CHE NLD 4.0 BDI SV N ISR PRT DNKNOR 1.4 RWA LT U FIN SW E 0 0 LAO Low Lower-Middle Upper-Middle High 5 6 7 8 9 10 11 12 ($148) ($403) ($1,097) ($2,981) ($8,103) ($22,026) ($59,874) Labor force participation GDP per capita 2018, constant 2010 US$ (Logs: upper numeral. Absolute value: lower numeral) Years of schooling OECD East Asia and Pacific Total factor productivity Europe and Central Asia Latin America and Caribbean Middle East and North Africa South Asia Sub-Saharan Africa Source: Authors’ simulations using LTGM and LTGM-TFP extension. Source: Authors’ simulations using LTGM and LTGM-TFP extension. Note: Labels use International Organization of Standardization (ISO) country codes. 4 Research & Policy Brief No.39 low-income, and high-income countries. Decomposition of the occupy different economic spaces than men, in terms of jobs loss reveals that the economic loss in middle-income and and sectors, partly because of different care and housework high-income countries is driven by the direct and indirect responsibilities as well as varying access to markets and impacts from the gender gaps in labor force participation, while institutions (World Bank 2011). For instance, women in the loss in low-income countries is driven more by the gender Malaysia cite housework, including child and elder care, as the gaps in years of schooling than labor force participation. Panel main reason they do not participate in the labor force, and B shows that the two regions with the largest and the second when they do work, they still “work” more than men, taking on largest gender gaps in labor force participation (figure 2), the relatively more hours of care work (World Bank 2019; Khazanah Middle East and North Africa (MENA) and South Asia (SA), have Research Institute 2019). Women’s time can be released by the largest economic loss, ranging from 29 percent to 42 expanding the availability, quality, and affordability of child and percent of the potential GDP per capita that could have been elder care, especially for the urban poor (World Bank 2019). For achieved if there had been no gender gaps in education and this, it is crucial to place a higher value on care work, which is labor force participation. vital for any society to function and thrive. The International Labour Organization (ILO), for instance, has put forth policy Policy Recommendations to Address Gender Inequality recommendations to “recognize, reduce, redistribute unpaid care work; reward paid care work by promoting more and As the discussion and simulations in this brief suggest, there decent work for care workers; and guarantee care workers’ can be substantial gains to economic growth from reducing representation” (ILO 2018). Improving economic opportunities gender inequality, particularly in labor force participation. The for women also involves removing legal barriers, especially World Bank’s 2011 World Development Report on gender discriminatory laws, for example, regarding land and ownership equality and development highlights four broad priority areas rights and in employment. Women still have only three-fourths for policymakers in tackling gender inequality: (1) reducing the legal rights of men, according to the 2020 edition of the gaps in human capital endowments; (2) improving women’s World Bank’s annual survey on Women, Business and the Law economic opportunities; (3) shrinking gender differences in (World Bank 2020). The third priority area—shrinking gender voice; and (4) limiting the perpetuation of gender inequality differences in voice—requires increasing women’s voice in across generations (World Bank 2011). society, for example, in political representation, judiciary, corporations, and professional associations. 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