Poverty and Gender in Malawi A background paper for the Poverty Assessment for Malawi Poverty and Gender in Malawi A background paper for the 2021 Malawi Poverty Assessment World Bank © 2021 Poverty and Equity Global Practice / The World Bank 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org This work is a product of the staff of The World Bank with external contri- butions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, 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 en- dorsement 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. Any 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. ACKNOWLEDGEMENTS This note was prepared by Melanie Gross (Con- Yaa Pokua Afriyie Oppong (Sector Leader). The sultant) and Miriam Muller (Social Scientist) team gratefully acknowledges comments and as a background paper for the 2021 Malawi inputs received from Pierella Paci (Practice Poverty Assessment with valuable contribu- Manager), Violette Mwikali Wambua (Senior So- tions from German Caruso (Senior Economist) cial Specialist), William G. Battaile (Lead Econ- and Lina Marcela Cardona (Economist). The omist), Inaam Ul Haq (Program Leader), Marcos work was closely coordinated with the 2021 Puig Insúa (Consultant), and Ursula Casabonne Malawi Gender Assessment team, led by M. (Consultant). TABLE OF CONTENTS Acknowledgements 3 1. Introduction and framework 7 2. The Intersection of Poverty and Gender in Malawi 11 3. Gender Disparities in Economic Opportunities and Outcomes 21 Labor force participation and wage employment 21 Gender disparities in the agriculture sector 27 Household businesses  34 Beyond labor income—transfers and the potential to alleviate poverty  36 4. Endowments: Essential Inputs to the Formation of Human Capital 40 Staying in school matters—girls at a disadvantage 40 Reproductive health 44 Disproportionate effect of HIV-AIDS on women in Malawi  48 5. Women’s Agency: A Crucial Driver behind Outcomes of Well-Being 52 Legal context 52 Violence against women and girls—a negation of their human rights 53 Child marriage—a specific form of violence against women that limits girls’ prospects in multiple dimensions of well-being 58 Women’s limited decision-making in private and public spheres  60 6. In Closing  64 Appendix A Data and Poverty Measurement Details 67 Appendix B Methodology and Data 70 Appendix C Women, Business and the Law 2021 72 References 76 5 1. Introduction and framework Over the past several decades, Malawi has seen during core productive and reproductive stag- important improvements in several key devel- es of life. Furthermore, households composed opment outcomes and a narrowing of gender of only one female adult with children are the gaps. Life expectancy has increased significant- poorest among all household compositions. Re- ly over the last 30 years, infant mortality rates latedly, households with children are consistent- decreased far beyond the Sub-Saharan Africa ly poorer, and the more children in a household, average between 1990 and 2018, and mater- the higher its probability of being poor. nal mortality rates have been reduced by more Therefore, an essential foundation of inclu- than half since 2000. Also, Malawi experienced a sive and sustainable growth, gender equality, steep drop in fertility from 6.7 births per woman is also deeply interconnected with and instru- in 1990 to 4.1 in 2018, decreasing much faster mental to poverty reduction. Gender disparities than the regional average. Likewise, it has made have negative development implications—not enormous strides in education: since school only for women but also for their families (par- fees were banned for publicly financed primary ticularly the next generation) and their entire schools in 1994, primary completion rates have societies (World Bank 2012; Mateo Díaz and Ro- increased from 36 to 85 (2019) percent for girls, dríguez-Chamussy 2016, World Bank 2018a). and 46 to 76 (2019) percent for boys. This paper presents an analysis of the intersec- Despite those improvements, the latest tion of poverty and gender, and discusses how household survey for Malawi (the Fifth Integrat- gender disparities contribute not only to gen- ed Household Survey [IHS5], 2019–20) confirms dered poverty in Malawi but also to poverty in a large gender disparity in poverty rates, with general. women more likely to be poor—especially single The paper is based on the analytical frame- mothers and women during the core productive work put forward in “Poverty Assessments and stages of life. Malawian women are more like- Gender Equality—A Guidance Note for Pover- ly than men to live in poor households starting ty Economists” (de Paz and Muller 2021). The in their mid-20s and continuing until their 50s; framework builds on the World Development hence, they are likelier than men to be poor Report 2012: Gender Equality and Development 7 Poverty and Gender in Malawi and argues not only that the three dimensions men throughout the course of their lives, in- of gender equality put forward there (endow- cluding their agency within the family and their ments, economic opportunities, and agency) communities; in addition, such investments are interconnected but also that progress in provide important foundations for women’s each of those dimensions stimulates progress access to economic opportunities. Similar- in the other dimensions (see Figure 1.1). For in- ly, women’s agency influences their ability to stance, human capital investments (health and build their human capital and take up economic education) affect the outcomes of women and opportunities. Figure 1.1. Framework of analysis Nonmonetary dimensions Gender gaps in endowments of poverty/drivers Gender gaps Inclusive Monetary Human capital investments in economic opportunity growth poverty Limited agency of women Intersectionality: rural, indigenous, conflict-a ected women, etc. Source: Based on de Paz and Muller 2021. Using data from the IHS5, we present a di- promoting or blocking access to quality eco- agnosis of poverty in Malawi, together with nomic opportunities, they constitute essential several related topics, disentangling elements dimensions driving poverty outcomes in terms that may contribute to nonmonetary aspects of of monetary aspects, because labor income is poverty. Gendered disparities in opportunities to one of the main contributors to an individual’s accumulate human capital and assets, to exer- standing with respect to the poverty line. cise agency, and to be economically active and For most of the paper, the analysis relies on productive will be assessed in depth. On one data from the IHS5, which has four separate hand, outcomes in endowments, human capital sections: household questionnaire, agriculture investments, and agency represent fundamen- questionnaire, fisheries questionnaire, and com- tal nonmonetary dimensions of poverty that are munity questionnaire. Our analysis uses the first important to look at when assessing multidi- two questionnaires extensively. In addition, the mensional poverty in and of themselves. On the poverty rates exposed here were estimated for other hand, given their important role in either the 2021 Malawi Poverty Assessment using the Poverty and Gender in Malawi 8 expenditure modules of the household ques- presents the data and empirical strategy. Chap- tionnaire of the IHS5. Finally, some other sourc- ter 2 presents poverty data and discusses the es such as the School to Work Transition Survey intersection of poverty and gender. Poverty by (SWTS),1 Demographic and Health Surveys,2 the household composition is essential for under- Joint United Nations Programme on HIV/AIDS standing gendered differences in poverty. From (UNAIDS),3 and the World Development Indica- there, chapter 3 explores gender disparities in tors4 were also consulted for particular topics economic opportunities, following the analytical not covered in the IHS5. framework cited earlier. We will then move to The paper, which serves as a gender back- potential drivers of economic outcomes: endow- ground paper for the 2021 Malawi Poverty ments (chapter 4) and agency (chapter 5). The Assessment, is structured as follows. It first last section offers conclusions. 1 The SWTS is a unique survey instrument that generates relevant labor market information on young people aged 15 to 29 years, including longitudinal information on transitions within the labor market. The SWTS thus serves as a unique tool for demonstrating the increasingly tentative and indirect paths to decent and productive employment that today’s young men and women are facing. 2 Demographic and Health Surveys are nationally representative household surveys that provide data for a wide range of monitoring and impact evaluation indicators in the areas of population, health, and nutrition. 3 UNAIDS leads the world’s most extensive data collection on HIV epidemiology, program coverage, and finance and publishes the most authoritative and up-to-date information on the HIV epidemic. Under a mandate from the United Nations General Assembly, UNAIDS works with all countries to collect and analyze data on their AIDS responses and to help build the capacity to generate and use strategic information. 4 For more on the World Bank’s World Development Indicators, see https://datatopics.worldbank.org/world-development-indicators/. 9 Poverty and Gender in Malawi Poverty and Gender in Malawi 10 2. The Intersection of Poverty and Gender in Malawi Malawi’s Fifth Integrated Household Survey percent; rural Central, 62.8 percent; and rural (IHS5, 2019–20), the most recent survey, shows Southern, 56.7 percent). In addition, significant disparities in poverty by gender, region, and age gaps arise when looking at poverty through the group. According to the IHS5, poverty among life cycle. As in other African countries, Malawi- women, measured by the share of women who an women are more likely than men to live in live in poor households, was 51.4 percent where- poor households starting in their mid-20s and as that share was 50.0 percent for men. While continuing until their 50s (World Bank 2018a). small, this difference is statistically significant1. Women are therefore likelier than men to be In addition, there are relevant differences in poor during core productive and reproductive poverty among regions: the probability of being stages of life (Figure 2.1). In addition, among the poor in urban regions is much lower (19.2 per- elderly population, the poverty rate for women is cent) than in rural regions (rural Northern, 35.9 again higher than that for men. 1 Poverty data are preliminary and will be updated with the National Statistical Office updated data. 11 Poverty and Gender in Malawi Figure 2.1. Poverty rates, by age group 70 60 50 (Percentage) Poverty rate 40 30 20 10 0 - 9 ars - 1 ars - 1 ars - 2 ars s - 3 ars s - 4 ars - 4 ars - 5 ars s rs s rs 75 ars s - 2 ar - 3 ar - 5 ar - 6 ar ar a a ye ye ye 20 9 ye 25 4 ye ye 35 4 ye ye ye ye 55 4 ye ye 65 4 ye ye ye ye -4 4 9 9 4 9 9 9 4 + -6 -7 0 5 10 15 30 40 45 50 60 70 Male Female Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. Such gender disparities are in line with find- (Muñoz et al. 2018). In addition, other measures ings by Muñoz et al. (2018), whose analysis of (for example, those based on consumption) that harmonized data points in Sub-Saharan Africa consider the allocation of resources within the shows that, for the 20–34 age group, the average household can help to build a more accurate gender poverty gap is as much as 7.1 percentage picture of poverty as experienced by individuals points. This pattern suggests that care respon- (World Bank 2018a). sibilities for children combined with constraints Similar results can be found in the IHS5 data, in economic opportunities may be major vul- which show that households composed of only nerability factors for women. When comparing one female adult with children are the poorest different types of household compositions, sole among all household compositions. Households female earner households make up the largest with one female adult2 are particularly vulnera- share of poor households in Sub-Saharan Afri- ble to poverty (56 percent; Figure 2.2) and even ca (SSA), and one-adult female households with more so if there are children in the household children are more prevalent among the poor (59 percent; Figure 2.3). In contrast, households 2 Households can be categorized by their demographic composition, particularly by the number of adults in the house- hold. A “One adult female” household is a household with only one adult, in this case a woman, and with or without children. The same happens with “One adult male” households, in which the only adult is a man and there could also be children in the household. Other categories are two adults, multiple adults, and only seniors. In all cases, the category is based on the number of adults in the household and always allows for having or not having children in the household. Poverty and Gender in Malawi 12 with one male adult have only a 33 percent than the female equivalent. Therefore, gender probability of being poor; even with children, and household composition seem to be determi- their poverty rate is 5 percentage points lower nants for poverty. Figure 2.2. Poverty rates, by household Figure 2.3. Poverty rates, by demographic composition presence of children 56 53 55 52 50 (Percentage) Poverty rate (Percentage) Poverty rate 33 11 11 One adult Other Multiple Two One adult Only No children Children in female adult adults male seniors in household household Source: Calculations based on Malawi’s Fifth Integrated Source: Calculations based on Malawi’s Fifth Household Survey, 2019–20. Integrated Household Survey, 2019–20. Figure 2.4. Poverty rates, by presence of children and household composition 59 50 52 53 55 (Percentage) Poverty rate 15 11 16 11 6 One adult One adult One adult One adult Two Two Multiple Multiple Only Other, female, no female, male, no male, adults, no adults, adults, no adults, seniors children children children children children children children children children Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. 13 Poverty and Gender in Malawi It is important to note that the concept of households with children are consistently poor- household headship does not provide a fully ac- er. The probability of being poor for a household curate picture of the intersection between poverty with children rises to 53 percent, whereas that and gender.3 First, many more women live in what probability is 11 percent for households without would be traditionally described as “male-headed children (Figure 2.4). Similarly, the more children households.” Second, the concept of female head- in the household, the higher its probability of be- ship may conceal a mix of widows and better-off ing poor.4 In this context, the relevance of high wives of migrant workers—women who have very fertility and high adolescent pregnancy rates different backgrounds. In the absence of individ- in conjunction with poverty becomes apparent. ual-level poverty data, it is therefore important Malawi exhibits high fertility rates: in 2018, the to use household survey data to analyze poverty fertility rate was 4.2 births per woman, slightly incidence on the basis of household typologies lower than the SSA average of 4.7 and far above that are neutral to social norms: demographic and the world average of 2.4 births per woman. Con- economic compositions, such as those used in the sequently, Malawi has a very young age struc- previous graph (Muñoz et al. 2018). ture—56 percent of the population is under the Other demographic characteristics are also age of 20 (UN DESA 2017) (Figure 2.5)—which is important determinants of poverty because highly related to poverty. Figure 2.5. Demographic pyramid 100+ -0 0 -0 0 -0 0 -0 0 80–84 -0 0 -0 0 Age (years) -0 0 -0 0 60–64 -0 0 -0 0 -0 1 -1 1 40–44 -1 1 -2 2 -3 3 -4 4 20–24 -4 4 -5 5 -6 6 -7 7 0–4 -8 8 -10 -5 0 5 10 Percentage of population Men Women Source: UN DESA 2017. 3 The headship concept merges women with different marital statuses, reflecting demographic rather than gender differences. It also does not account for the reasons why households are headed by women/men, reflecting social norms—and therefore varying across countries. 4 No children, 11 percent; one child, 27 percent; two children, 43 percent; three children, 53 percent; four children, 66 percent; and five children or more, 74 percent. Poverty and Gender in Malawi 14 Although Malawi’s overall fertility rate is high, now significantly below the SSA average of 4.2 progress has been made over the last 30 years in (WDI 2018) and lower than in Tanzania (4.5 births reducing it (Figure 2.6). Although originally above per woman, 2016), Guinea (4.3 births per wom- the SSA average, Malawi’s fertility rate decreased an, 2018), Zambia (4.0 births per woman, 2018), at a fast pace for many years and has been below and Zimbabwe (3.6 births per woman, 2015).5 the SSA average since about 2010. In addition, Decreases in wanted fertility rates together with the wanted fertility rate has declined significantly increased use of contraception point toward a from 4.5 children in 2010 to 3.4 in 2017 and is sustained drop in the fertility rate in the future. Figure 2.6. Fertility rate, Figure 2.7. Adolescent fertility rate, 1990–2018 1990–2018 8 200 Births per 1,000 women Births per woman 6 150 4 ages 15 - 19 100 2 50 0 0 1990 1995 2000 2005 2010 2015 1990 1995 2000 2005 2010 2015 Year Year Malawi Sub-Saharan Africa Malawi Sub-Saharan Africa Source: World Development Indicators Source: World Development Indicators Although overall fertility rates have declined, en and men show similar poverty rates, though childbearing among adolescent girls in Malawi still favoring men. However, separated, divorced, remains high at a rate of 132 births per 1,000 and widowed women have a significantly higher women aged 15–19 in 2018, substantially great- probability of being poor than their male peers er than the average for SSA countries (101 births (Figure 2.8). Gaps rise up to 18 percentage points per 1,000 women). Despite some progress over (widowed), 31 percentage points (separated), and the last three decades (see Figure 2.7) and fall- 35 percentage points (divorced). These findings ing overall fertility rates, teenage pregnancy is are consistent with other studies showing that, still an important issue in the country. for African women, marital rupture frequently When analyzing poverty by sex and marital sta- entails a loss of the economic means and support tus, one finds major poverty gaps. Married wom- that are acquired through, and conditional on, 5 Data are from the World Bank’s World Development Indicators data set, for the year indicated for each country. See https://datatopics.worldbank.org/world-development-indicators/. 15 Poverty and Gender in Malawi marriage—including access to productive assets among the never married population (which here (such as land) and the marital home (Djuikom and includes children) female poverty rates are only van de Walle 2018; Kevane 2004). Conversely, slightly higher than male poverty rates. Figure 2.8. Poverty rates, by marital status and gender 57 56 50 52 51 53 46 43 44 (Percentage) Poverty rate 28 21 21 Monogamous Polygamous Separated Divorced Widor or Never married or married or widower married non-formal non-formal union union Male Female Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. Two customary systems, one matrilineal and patrilineal (95.2 percent of persons in the rural one patrilineal, can be distinguished in Mala- Northern region report living under patrilineal wi. Under the matrilineal system, chieftaincy is tradition), whereas the rural Southern region handed down through the female line and so is has a stronger presence of the matrilineal sys- land. Under the matrilineal system of marriage, tem (63.3 percent of people living in the rural a man’s rightful heirs to his land are his sister’s Southern region report having married under children (Pachai 1978). Under the patrilineal the matrilineal tradition). Urban areas as well as system, land is transferred from fathers to sons, the rural Central region are somewhat mixed. and power and decision-making capacity are as- Although the matrilineal system prevails signed to the man rather than the woman. among 47.9 percent of people, no significant ad- In the IHS5 (2019–20), 51.7 percent of persons vantages in terms of absence of poverty or labor reported having married under the patrilineal force participation are found for women in those system and 47.9 percent under the matrilin- households. In that sense, even though chieftain- eal tradition. The latter system characterizes cy and land are handed down through the female land transfers within the Central and Southern line, women do not seem to be better off under regions (Ng’ong’ola 1982; Pachai 1978; Peters this inheritance system—at least when it comes 2010). Malawi’s rural Northern region is mainly to poverty and labor force participation. A reason Poverty and Gender in Malawi 16 for this could be that both matrilineal and patri- obligated to take care of their children because lineal systems6 operate in Malawi’s ethnic groups tradition dictates that the maternal uncle is the and both perpetuate discrimination against one who is supposed to assume that responsibil- women in the family (Kamyongolo and Malunga ity (White 2007; WLSA 2002). 2011). For example, wives even in the matrilin- According to data from the IHS5, among eal system are often victims of discriminatory agricultural households under the patrilineal inheritance practices in which the deceased hus- system, poverty is 5 percentage points higher band’s family unlawfully takes property. In fact, when the land manager is female than when it has also been argued that the patrilineal sys- he is male (Figure 2.9). By contrast, under the tem may actually provide enhanced security to matrilineal system the gap is only 1 percentage women and children because men feel an obli- point, again favoring male-managed agricultur- gation to take care of their families. Conversely, al households. This means that the gap is more in the matrilineal system, because of the matri- emphasized in the patrilineal system but still local residence, men may be discouraged from exists in the matrilineal system, where one may making any investments and may also feel less have expected women to be better off. Figure 2.9. Poverty rates, by gender of land manager and by customary system 60 57 57 57 56 55 54 (Percentage) Poverty rate 52 50 45 Patrilineal Matrilineal Total Female land manager Male land manager Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. 6 In Malawi there are two major systems of contracting marriages at custom: the dominant matrilineal system, which prevails in most parts of the Central region and in most parts of the Southern region, and the patrilineal system, which prevails in the whole of the Northern region, in certain parts of the Central region, and also in certain parts of the Southern region (Chigawa 1997). Under the matrilineal system of marriages there is no payment of dowry, but various gifts may be exchanged between the contracting parties. Under the patrilineal system of marriage, dowry is paid by the man’s family to the woman’s family in the form of livestock or money. 17 Poverty and Gender in Malawi The 2016 Malawi Poverty Assessment found be quite significant (Beegle and Poulin 2013). that poverty in the country is predominantly ru- In the IHS5, about 77 percent of married wom- ral and primarily associated with agriculture en who have moved at least once in their lives7 and farm activities. The IHS5 reveals that pov- did so because they got married. Although this erty in rural areas stood at 57 percent in 2019 share is higher among women married under but at 19 percent in urban areas. In the last de- the patrilineal tradition (81.7 percent), it is still cade, however, an important proportion of the quite significant among those under the matrilin- rural population has migrated to urban areas in eal tradition (67.9 percent)—and somewhat sur- search of better opportunities. According to the prisingly still higher than the respective share most recent national censuses, the country’s of movers among men in the matrilineal tradi- urban population increased from 34 percent in tion (Figure 2.10). Among men, only 15.5 percent 2008 to 41 percent in 2018. of those married under the patrilineal system The data show that almost the same share moved as a consequence of marriage, whereas of women as of men respond that they have al- 48.6 percent under the matrilineal system did. ways lived in the village or urban location where Therefore, regardless of the tradition, fewer men they lived at the time of the survey (83.6 percent than women moved because of their marriage. of men and 82.1 percent of women). Neverthe- By contrast, moving for work-related reasons is less, the reasons reported for moving away from more frequent among men than among women. their original villages differ by gender. Peoples’ This finding is true under both marriage sys- motivations for migration are not always linked tems, yet it is stronger under the patrilineal one. to economic gains; in fact, in Malawi, migration Other studies, such as the Marriage Transitions associated with marriage has been found to in Malawi8 project, have found the same result. 7 In IHS5, the question about reasons for moving is asked of all people who claim to “have not always lived in the same village,” meaning that they have moved at least once. 8 The Marriage Transitions in Malawi project consists of a longitudinal panel data set on young women and men in cen- tral Malawi from 2007 to 2009. Studies based on this data, such as Beegle et al. (2016), showed that more young men than young women moved for work-related reasons. Poverty and Gender in Malawi 18 Figure 2.10. Reasons for moving from village, by gender and marriage tradition 90 81 67 Share of respondents (%) 60 48 30 21 15 15 16 10 10 12 7 9 6 9 5 5 3 2 2 2 2 2 1 1 0 Marriage Parents To live with To look for To look for To start a moved relatives work land to farm new job or business Male - Patrilineal Female - Patrilineal Male - Matrilineal Female - Matrilineal Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. After their move, migrants reside in wealthier (Beegle and Poulin 2013). In the data, female households compared to those who did not move. movers are less likely to be currently attending Although poverty rates among both female and school at follow-up (of the panel data) than are male migrants are lower than among nonmi- nonmovers, consistent with the finding that ad- grants, nonmonetary dimensions can affect fe- olescent girls and young women who moved to male migrants. For example, it is extremely rare another village between one round and the other for married women to continue to attend school were more likely to be married by 2009.9 9 Panel data from Marriage Transitions in Malawi, 2007–09 (https://microdata.worldbank.org/index.php/catalog/3462). 19 Poverty and Gender in Malawi 3. Gender Disparities in Economic Opportunities and Outcomes Good-quality jobs are important for women, their ences in poverty. This chapter discusses gender families, and communities –they help pull families disparities in the world of work across different out of poverty. Yet gender disparities in econom- dimensions: labor force participation, employ- ic opportunities, earning, and productivity persist ment, enterprises, farming, and job characteris- in the world of work in Malawi, facilitating differ- tics such as formality, earnings, and job quality. LABOR FORCE PARTICIPATION AND WAGE EMPLOYMENT There are wide gender gaps in women and less in the labor force than do men of the same men’s economic opportunities in terms of labor groups (Figure 3.1, Figure 3.2, and Figure 3.3). force participation, earnings, and control of pro- In general, participation rates do not vary much ductive assets. In terms of labor force participa- across gender; labor force participation is high tion, Malawi’s Fifth Integrated Household Survey across all age groups and regions, and inde- (IHS5, 2019–20) finds that 80.2 percent of men pendent of marital status. Nevertheless, par- compared to 71.9 percent of women (above age ticipation of highly educated women (who have 15) are in the workforce. Among younger indi- completed secondary or more) is 9.3 percentage viduals (16–24 years old), the gap is slightly points lower than that of their male peers, and smaller: labor force participation is 67.9 percent the gender gap between women in the highest in- for men and 61.2 for women. In addition, accord- come quintile and their male peers is even larger ing to 2017 data from the World Development In- at 13.6 percentage points. Additionally, women in dicators, 41.4 percent of young women are not in urban areas participate less than men: 58.5 per- education, employment, or training, in compari- cent (women) versus 75.5 percent (men). And the son to 23.6 of their male peers. gender gap in labor force participation is larg- Women in urban regions, in higher income er among the nonpoor (11.4 percentage points) quintiles, and with higher education participate than among the poor (4.9 percentage points). 21 Poverty and Gender in Malawi Figure 3.1. Labor force participation, Figure 3.2. Labor force participation, by quintile by highest achieved educational level 79 80 80 81 81 80 82 79 76 74 76 76 73 71 67 Labor force partcipation 70 66 68 Labor force partcipation (Percentage) (Percentage) None Some primary Completed Completed primary secondary Q1 Q2 Q3 Q4 Q5 or more or more Expenditure quintiles Educational level Male Female Male Female Source: Calculations based on Malawi’s Fifth Integrated Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. Household Survey, 2019–20. Figure 3.3. Labor force participation, by region and gender 83 82 77 80 75 74 74 Labor force participation 59 (Percentage) Urban Rural North Rural Centre Rural South Region Male Female Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. Poverty and Gender in Malawi 22 Although labor force participation as found In ganyu labor, for which data are available only in Malawi’s IHS5 is notably high, the number of for annual days worked, men also work more average hours worked is low in general and par- days than women (87 days a year versus 63 days ticularly low for women. On average, a work- a year) (Figure 3.5). These gender disparities in ing person works 593 hours a year,1 excluding hours worked persist across highest education ganyu2 labor. This number is much higher for level completed and age groups. In sum, men men (736 hours) than for women (466 hours). No spend more mean annual hours3 in economic ac- major gender differences in hours worked can tivity than women. Gaps in total time allocation to be found in agriculture, where most households economic activities are similar across regions: produce for own consumption. On average, bigger larger in urban regions (1,481 hours for men ver- gaps are found in activities with higher returns: sus 957 hours for women) and smaller in rural women work 214 hours less per year in wage regions (Northern, 656 hours for men versus 470 jobs (about 4.5 hours less per week) and 405 hours for women; Central, 603 hours for men hours less when working in businesses than men versus 378 hours for women; and Southern, 600 do (about 8.5 hours less per week) (Figure 3.4). hours for men versus 403 hours for women). Figure 3.4. Annual hours worked, Figure 3.5. Annual days worked by activity in ganyu 1600 Annual days, people aged 15 and older 100 1295 1366 87 Annual hours, people 1152 aged 15 and older 1200 80 890 63 800 60 400 230 221 40 0 20 Household Wage Agriculture business employment 0 Male Female Male Female Source: Calculations based on Malawi’s Fifth Integrated Household Source: Calculations based on Malawi’s Fifth Survey, 2019–20. Integrated Household Survey, 2019–20. 1 Total hours are calculated by summing the amount of hours worked in agricultural activities, wage jobs, and nonagri- cultural businesses. These are the only activities for which data are available on annual time allocation. 2 “The word ‘ganyu’ is widely used in Malawi to describe a range of short-term rural labour relationships (casual labor), the most common of which is piecework weeding or ridging on the fields of other smallholders, or nonagricultural estates” (Whiteside 2000). 3 Total weekly hours are calculated as the sum of hours allocated to agriculture, livestock, forestry, household business- es, ganyu, wage employment, fisheries, and others. 23 Poverty and Gender in Malawi Moreover, women are overrepresented in high- mal nonfarming and of both formal and informal risk forms of labor. When it comes to diversifica- nonfarming activities. Conversely, more men (12.4 tion of economic activities, half the population ages percent) than women (4.1 percent) are salaried 15 and above do farming activities plus another workers, and the rate of nonworking women is informal nonfarming activity (Figure 3.6). Women higher than that of men (10.0 percent versus 6.3 are more involved in riskier and lower-paying ac- percent)—all of which can be interpreted as indi- tivities such as nondiversified farming, whereas cations of lower-quality jobs among women com- men have higher proportions of farming plus for- pared to among men (Figure 3.7). Figure 3.6. Degree of diversification of work, by gender 50 49 Percent engaged in activity (%), 50 people aged 15 and older 40 30 18 20 10 10 10 10 6 7 8 7 7 10 2 2 0 Not working Nondiversified Diversified Farming + Farming + Formal NF Informal NF farming farming informal NF formal NF Male Female Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. Note: NF = nonfarming. Figure 3.7. Main work activity in the last 12 months, by gender Percent engaging in activity (%), 60 people aged 15 and more 49 20 12 16 10 12 11 6 4 Not working Wage Household Agriculture Ganyu employment business Male Female Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. Poverty and Gender in Malawi 24 The share of people working in formal wage living in rural areas do so (Figure 3.8). Overall, employment is even lower in rural areas, par- this pattern is similar for men, but the share of ticularly for women. Whereas 13.0 percent of men living in rural areas and working for a sal- women in urban areas work as employees for a ary is about 8.1 percent (versus 2.4 percent of wage or salary, only about 2.4 percent of women women in rural areas). Figure 3.8. Share of people working for a wage, salary, or commission in the last 12 months 35 31 Share of respondents (%), people aged 15 and more 30 25 20 15 13 12 9 10 6 5 3 2 3 0 Urban Rural North Rural Center Rural South Region Men Women Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. The Living Standards Measurement Study In the IHS5, almost half the female salaried Plus (LSMS+) program4 also provides results workers (48.3 percent) do not have a formal in labor market outcomes across gender. The contract, compared to 43.0 percent for men. comparisons across the LSMS+ and the IHS4 Therefore, not only are fewer women salaried (Fourth Integrated Household Survey, 2016–17) workers, but they also work under worse condi- show that the IHS4 leads to significantly lower tions. In addition, more men than women work in reporting of employment across a range of wage jobs that offer an old-age pension (25.7 percent and self-employment activities, with stronger for men versus 20.9 percent for women) and a effects for women and for a longer (12-month) disability pension (15.9 percent for men versus recall period. 10.3 percent for women). 4 The LSMS+ surveys are panel household surveys with an emphasis on agriculture in seven Sub-Saharan African coun- tries (including Malawi). These surveys contain gender-disaggregated data and, importantly, request responses to the questionnaire from all adult individuals within a household for themselves, instead of having the “most knowledgeable” individual in the household respond for all household members. 25 Poverty and Gender in Malawi Malawi’s labor market is also marked by oc- female salaried workers, add up to only 20 per- cupational segregation. One third of women cent among male salaried workers. By contrast, working for salary are cleaners or helpers, and more men than women are engaged in protective an additional 17 percent are teaching profession- services jobs as well as in mining, construction, als. These occupations, which account for half of manufacturing, and transport (Figure 3.9). Figure 3.9. Wage employment and job classification, by gender 40 34 35 Percentage engaging 30 in activity 25 15 17 20 13 12 10 15 9 8 9 7 6 10 5 2 2 5 0 0 0 Cleaners Protective Agricultural, Teaching Laborers Sales Building Heatlh and service forestry and professionals in mining, workers and related associated helpers workers fishery construction, trades professionals services manufacturing (excluding and transport electricians) Men Women Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. A recent qualitative study aiming to under- al schools, female students report having less stand the constraints to women’s equal partic- confidence and aspiration in engineering and ipation in Malawi’s roads sector identifies the vocational training in the roads sector. At the se- barriers to career progression in the sector at lection stage, women face gender bias in hiring each stage in the career cycle, focusing on at- and a difficult work environment, resulting in an traction, selection, retention, and advancement exodus of talent among women who could oth- (Muller et al. 2019). It yields insights into the erwise become the next generation of architects, multiple and overlapping factors embedded in engineers, and roads sector contractors. At the the socialization, learning, and hiring processes retention and advancement phase, women con- that result in high rates of attrition of women in front a difficult work environment in which they the engineering and roads-related technical field are sidelined from career advancement opportu- at different stages of the career cycle. This attri- nities, face sexual harassment, and have difficul- tion is often called the “leaky pipeline” in policy ty balancing work and family obligations because discussions about women in science, technology, many opportunities are in remote locations. engineering, and mathematics fields. From sec- Women not only are less involved in wage ondary school through university and vocation- employment but also earn less when they are Poverty and Gender in Malawi 26 involved. Women’s median annual income is the Southern region (urban and rural), median 396,000 Malawian kwacha (MK), whereas men’s wages are equal for men and women in the ru- median income is to MK 507,600. Nevertheless, ral Central region, and, interestingly, in the rural the picture is heterogeneous across regions Northern region, women earn higher median an- (Figure 3.10). Men’s median wages are higher in nual wages than men. Figure 3.10. Median annual wage, by gender and region 900000 768000 Median annual wage (mk) 576000 600000 540000 504000 468000 308571 360000 300000 300000 0 Urban Rural North Rural Centre Rural South Region Male Female Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. Note: MK = Malawian kwacha. GENDER DISPARITIES IN THE AGRICULTURE SECTOR Agriculture is the single most important sector Most land is inherited, owned, and operated in Malawi’s economy, with much of the popula- by men. According to the IHS5, 33 percent of tion highly dependent on agriculture, particular- plots owned by households are owned by men, ly subsistence farming. Participation rates in the 43 percent are owned jointly by men and wom- sector are high for both women and men (54.8 en, and 24 percent are owned solely by women. percent of Malawians above 15 years old work in At the same time, in almost half of households, agriculture according to the IHS5, 2019–20), but only men have the right to sell and to bequeath for women, the proportion working in agricul- land (47 and 47 percent) and in only 26 and 25 ture rises to 59.6 percent (10 percentage points percent of households do women have the exclu- above men). However, outcomes of their respec- sive right to sell and to bequeath, respectively. tive agricultural activities vary significantly be- Because the share of households in which men tween women and men. have the exclusive rights to bequeath and to sell 27 Poverty and Gender in Malawi is higher than the share of households in which than that of joint decision-making and the share they are exclusive owners, one can interpret that of male ownership is lower than that of male de- they are making decisions over female-owned cision-making, probably meaning that men have or jointly owned land. more power to make decisions regarding the Looking at regional figures within Malawi, land. On the one hand, the share of male owner- one finds that the share of households in which ship and decision-making is particularly high in the land is owned solely by women is very sim- the Northern rural region, where the patrilineal ilar to the share of households in which only system is mainly present. On the other hand, the women have the rights to sell and to bequeath rural Southern region, which is predominantly in all regions (Figure 3.11). On the contrary, in matrilineal, exhibits both higher female owner- general, the share of joint ownership is higher ship and higher female decision-making. Figure 3.11. Land ownership and decision-making, by gender a. Urban b. Rural North 60 58 58 60 Share of households (%) 49 Share of rhouseholds (%) 49 44 46 38 39 32 32 30 30 26 26 18 19 19 15 16 16 0 0 Owner Right to sell Right to bequeath Owner Right to sell Right to bequeath Solely by women Solely by men Jointly by women and men Solely by women Solely by men Jointly by women and men c. Rural Center d. Rural South 60 60 Share of households (%) Share of households (%) 46 46 44 44 43 43 35 34 33 32 32 31 30 30 25 24 22 22 22 22 0 0 Owner Right to sell Right to bequeath Owner Right to sell Right to bequeath Solely by women Solely by men Jointly by women and men Solely by women Solely by men Jointly by women and men Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. Similar findings also arise from the LSMS+ significantly less likely than their male counter- program: in Malawi, female landowners are still parts to have rights to sell and bequeath land. In Poverty and Gender in Malawi 28 the LSMS+ program, survey modules are asked and Udry 2008; Hill and Vigneri 2011; Quisumb- directly at the individual level, instead of at the ing and Otsuka 2001), other research detects household level. This means that, instead of ask- a multitude of reasons behind women’s lower ing a single person in the household about all its productivity that may vary by crop, ecological members, each individual person is interviewed. zone, and other characteristics, including differ- There are important benefits for interviewing ences in resource inputs, differences in invest- each individual member: for example, because ment incentives, both technical and allocative land ownership may not always equate to rights inefficiency, differences in access to household over land, such a distinction can be obscured resources and productivity augmenting resourc- when individuals do not report for themselves. es, differences in the intensity with which inputs In fact, in the LSMS+ survey, for each parcel, re- are applied, differences in land tenure security, spondents were asked about different types of and limited access to physical capital, land, and ownership and rights, and about decision-mak- scheme membership. ing in the case of agricultural parcels, finding What is behind gender disparities in agricul- that in many cases women own but do not make tural productivity in Malawi? Several studies im- decisions over their land. ply that women farmers’ relatively lower levels Additionally, a recent study by Kilic et al. of productivity can be explained by lower levels (2020) compares the Malawi LSMS+ with the of education and input use. Kilic, Palacios-López, IHS4, the latter of which asked questions of only and Goldstein (2015) find that female farm man- one “most knowledgeable” respondent in the agers are 25 percent less productive than their household. They find that the IHS4 resulted in male counterparts—with 82 percent of the dif- higher rates of exclusive reported and economic ference attributable to differences in endow- ownership of agricultural land among men, and ments. Contributing to the gender gap are (i) lower rates of joint reported and economic own- lower levels and returns to adult male labor ership among women.5 input on female managed plots, and (ii) higher Not only do fewer women own and make de- returns to inorganic fertilizers and a higher area cisions over land, but women are also less pro- under export crop cultivation on male-man- ductive. Karamba and Winters (2015) provide an aged plots. In addition, Asfaw and Maggio (2018) overview of the literature on gender disparities find that weather shocks affect more severe- in agricultural productivity in Sub-Saharan Af- ly households where land is solely managed rica. Although some studies find female pro- by women. They find that this vulnerability to ducers to be equally or more productive than shocks is linked to women’s land tenure secu- male farmers in specific contexts (Goldstein rity, because temperature shocks significantly 5 This comparison was possible because IHS4 was conducted at the same time, and with the same questionnaire format as the nondwelling land assets module in the LSMS+ but with a different interview approach. 29 Poverty and Gender in Malawi affect women’s welfare only in patrilineal dis- This is true for all expenditure quintiles and for tricts, where data show that investment in ag- both urban and rural regions. ricultural technologies is lower. The authors Productivity is strongly related to innova- suggest that, when women’s land tenure is em- tion, farm inputs, and farm machinery. Sub- bedded within customary norms, women may stantial differences arise among female- and be incentivized to invest more in climate-resil- male-managed land when it comes to farm ient technologies, which could decrease their inputs and agricultural activity results. In ag- vulnerability to extreme weather events.6 ricultural households where the land manager The IHS5 data reveal that the mean harvest- is a woman, the land size is smaller, fertilizers ed value of male-managed plots is 49.5 percent are less frequently used, fewer farm assets are higher than that of female-managed plots (Table owned, and fewer hours are allocated to agri- 3.1). In addition, plots managed solely by men culture. In addition, the IHS5 finds that the val- also have higher harvested values when con- ue of the physical capital (among owners) is 55 trolling for the planted area. The gap in mean percent higher in households where crops are harvested value per hectare is 11.4 percent.7 managed solely by men than solely by women. When performing a mean comparison t-test, As a result, hourly agricultural income, produc- one can find that the gap in mean productivity tivity (harvested value per hectare), and real between female vs male managers is signifi- per capita expenditure are significantly lower cant.8 In sum, this means that, for each planted in female-managed land. Consequently, pover- hectare, male-managed plots produce a higher ty for households with female-manage land is harvested value than female-managed plots do. significantly higher. 6 Some earlier studies suggest allocative inefficiency but no significant male–female differences in productivity, once differences in human capital and inputs are taken into account (Quisumbing 1996). 7 In some cases, the reported planted area, which is calculated as the sum of each crop’s planted area, is bigger than the reported plot size. Therefore, a new normalized planted area was computed by maintaining relative areas between crops and by normalizing the planted area to the total plot size. 8 For this comparison, the p-value = 0.000. Poverty and Gender in Malawi 30 Table 3.1. Differences in agricultural inputs and results Female land Male land manager manager Difference Total t-test Inputs           Land size (ha) 0.53 0.72 -0.18 0.66 *** Dummy: Fertilizer use, % 73 79 -6 78 *** Fertilizer use (kg) 68 108 -39.7 94 *** Fertilizer use (kg/ha) 190 202 -12.3 197 Count of coupons 2.5 2.5 0 2.5 Count of owned farm assets 4.3 6.2 -1.9 5.5 *** Annual growing time (hours) 202 250 -48 235 *** Annual harvesting time (hours) 61 89 -28 80 *** Annual planting time (hours) 240 298 -58 282 *** Total annual agriculture hours9 503 637 -134 596 *** Results           Agricultural income per hour (mk) 330 506 -176 445 *** Harvested value per hectare (mk) 347,886 382,608 -34,722 368,365 *** Count of crops 2.8 2.9 -0.1 2.9 ** Count of sold crops 0.7 1.0 -0.3 0.9 *** Poverty 60% 53% 7pp 56% *** Annual per capita real expenditure (mk) 179,387 196,130 -16,743 189,117 *** Total           Observations 3349 4390 -1041 7739 *** Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. Note: ha = hectare; kg = kilogram; MK = Malawian kwacha; pp = percentage point. *** p < 0.01, ** p < 0.05, * p < 0.10. With respect to innovation, Mutenje et al. sions on household food security. Both men and (2016) analyze the driving forces that enhance women have distinct responsibilities and are key farm households’ decisions to adopt agricultural decision-makers in the spheres of production cy- innovations and the implications of these deci- cle that they control, varying by cash crop and by 9 Total annual agricultural time is the sum of annual planting, growing and harvesting time. 31 Poverty and Gender in Malawi the culture of the community to which the house- This can be seen when regressing poverty and hold belongs (matrilineal, patrilineal). Under this harvested value (as dependent variables) on farming system, some decisions are made by land manager’s gender (Table 3.2, columns (1) men or women only and others are reached af- and (2)). However, such differences become ter consultations with household heads and oth- insignificant when controlling for farm inputs er members of the farm household. Women with and household and land characteristics (Ta- higher intrahousehold decision-making power ble 3.2, columns (3) and (4)). The differences index and more skills training usually influence in productivity could be interpreted as being greatly the adoption of agricultural innovations. due to women’s lower access to inputs such Spouse’s education level positively and signifi- as land size, fertilizers, seeds, coupons, farm cantly influences women’s participation in deci- assets, and time allocated to agriculture, rath- sion-making on agricultural resource allocation er than to women’s lack of productivity. This and technology choice. has relevant policy implications, because it The result of these various dynamics is that suggests that women are not less productive female-managed agricultural households are per se, but simply lack fundamental inputs for poorer and have worse agricultural outcomes. production. Poverty and Gender in Malawi 32 Table 3.2. Regression analysis on poverty and harvested value (1) (2) (3) (4) VARIABLES Harvested value Poverty Harvested value Poverty           Female land manager (dummy) -87,173*** 0.0620*** -5,700* 0.00791 (4,497) (0.0112) (3,108) (0.0109) Land size (ha) 148,822*** -0.0358** (4,285) (0.0150) Dummy: fertilizer use 35,997*** -0.0985*** (3,801) (0.0133) Fertilizer (kg/ha) 9.101*** -1.98e-05** (2.390) (8.44e-06) Used seeds (kg) 2,537*** -0.00168*** (108.5) (0.000380) Count of coupons 6,201*** -0.00534 (1,560) (0.00550) Count of owned farm assets 7,921*** -0.0212*** (498.9) (0.00174) Total annual agricultural hours 10.75*** 0.000134*** (3.166) (1.11e-05) Rainfall controls No No Yes Yes Household head and composition controls No No Yes Yes District controls No No Yes Yes Crop production categories controls No No Yes Yes Crop selling categories controls No No Yes Yes Constant 251,252*** 0.535*** -83,227** 1.089*** (2,770) (0.00692) (40,821) (0.143) Observations 8,099 8,272 7,866 8,034 R-squared 0.044 0.004 0.615 0.208 Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. Note: ha = hectare; kg = kilogram. Standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.10. 33 Poverty and Gender in Malawi Finally, differences in time use due to socially Although Malawi’s IHS5 does not contain data ascribed gender roles influence the division of on time spent in home production and care work, labor within a household, which also may have it does reveal that women spend more time col- consequences for agricultural productivity. As lecting water and firewood than men. On average, seen in Table 3.1, time allocated to agriculture both women and men spent about one hour col- is lower in female-managed agricultural house- lecting water and one hour collecting firewood in holds. When women spend more time in home the reference day. The LSMS+ program finds sim- production, reproduction, and care work, it may ilar results, but it reveals that both women and have implications for their farm production. In men spend greater time on collecting activities contexts with low access to electricity and wa- than found by other national surveys conducted ter, women also tend to spend more time than in Malawi. The differences between surveys were men collecting firewood and water. particularly high for women. HOUSEHOLD BUSINESSES Malawi’s nonfarm economy is characterized by percent of the initial capital came from own-sav- its household businesses more than by its enter- ings from other activities and 8.1 percent from prises. These small businesses are mainly orient- loans. For their female peers, a lower proportion ed toward direct consumers (89 percent). These of initial capital (46.7 percent) came from sav- businesses are highly informal, with only about 2 ings and a higher proportion (15.8 percent) from to 6 percent registered and with registration rates loans, which usually have a higher cost. In ad- varying across the different registration authori- dition, more household businesses run only by ties. The three different types of registration au- women than by men were not operational at the thorities in Malawi are the Register of Companies, time of the survey. Both one female adult and one the Revenue Authority, and the Local Assembly. male adult household businesses are mainly in The share of registered businesses is very low, retail trade, but women’s household business- regardless of the registration authority. es are much more involved in the manufacture “One female adult”10 households run 13 per- of food products (23.5 percent) than men’s (5.6 cent of household businesses, and only 4 per- percent). Last, monthly revenues are 25 percent cent are run by “one male adult” households. In higher in one adult male household businesses the one male adult household businesses, 52.6 than in their female equivalent (Figure 3.12). 10 Recall that these types of household are composed of only one adult and any number of children. Poverty and Gender in Malawi 34 Figure 3.12. Last operational month’s median revenues, by household composition 25000 20000 20000 18000 Median revenues (mk) 15000 10000 10000 8000 8000 5000 0 One adult One adult male Two adults Multiple adult Only seniors female Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. Financial services are essential inputs to the centage points, with only 30 percent of women productivity and sustainability of firms; in Ma- owning an account compared to 38 percent of lawi, however, women have low access to such men (Figure 3.13). That gap has emerged only services. In 2017, the gender gap in access to since 2011, as men’s access to account own- account ownership with a financial institution ership increased more significantly than wom- or mobile money service provider was 8 per- en’s access did. Figure 3.13. Account ownership at a financial institution or with a mobile-money- service provider, 2011–17 40 % of population ages 15+ 30 20 10 0 2011 2014 2017 Year Women Men Source: World Development Indicators (https://datatopics.worldbank.org/world-development-indicators/). 35 Poverty and Gender in Malawi The IHS5 finds that 23 percent of one male banks. Furthermore, one female adult house- adult and 32 percent of one female adult house- holds borrow, on average, 31 percent less mon- holds borrow on credit but that one female adult ey than one male adult households do. households do so more frequently for starting In addition, one male adult households own businesses (23 percent) than their male equiv- more durable goods than one female adult alent (12 percent). By contrast, one male adult households. In particular, a higher share of the households more frequently borrow to purchase former own beds (33 percent of one male adult inputs for tobacco or other cash crops (6 per- households versus 19 percent of one female cent) than their female equivalent (2 percent). adult households), tables (22 percent versus 16 Also, more one male adult households borrow percent), radios (21 percent versus 13 percent), on credit for consumption. In addition, a high- televisions (6 percent versus 5 percent), bicy- er share of one female adult households bor- cles (32 percent versus 17 percent), irons (12 row from village banks (46 percent) and money percent versus 7 percent), and solar panels (14 lenders (8 percent) than one male adult house- percent versus 10 percent). This means that holds (26 percent from village banks and 5 from one male adult households tend to have more money lenders). These village banks and money access to durable goods than one female adult lenders tend to lend at higher interest rates11 households. Nevertheless, for those house- than commercial banks or friends and relatives. holds owning the different types of durable In fact, the monthly average interest rate is 7 goods, the number of units and the values of percent for village banks, and only 2 percent for such items do not differ much between house- family and friends as well as for commercial hold compositions. BEYOND LABOR INCOME—TRANSFERS AND THE POTENTIAL TO ALLEVIATE POVERTY In Malawi, households composed of only se- dian value of total transfers.12 Particularly, one niors, followed by households with only one female adult households, generally poorer and female adult, are recipients of the highest me- more vulnerable households, receive a slightly 11 Computed as the value of total final payment over the initially borrowed value. The monthly average interest rate was computed as the total final payment over the initially borrowed value, divided by the length of the loan (the number of months that passed between asking for the loan and repaying it). 12 The total transfer amount of a household is composed of the monetized sum of free maize, free food, free work inputs, a scholarship for secondary education, a scholarship for tertiary education, cash from the government, cash from non- government institutions, the Malawi Social Action Fund, work programs, and others. Poverty and Gender in Malawi 36 higher median total transfer than only one male female adult versus MK 24,000 per year for one adult households (MK 28,000 per year for one male adult; Figure 3.14). Figure 3.14. Median received transfers by household composition 35000 31000 Value of transfers received per 30000 28000 24500 24000 25000 household (mk) 21000 20000 15000 10000 5000 0 Only seniors One adult Multiple adults One adult Two adults female male Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. On top of differences in total received medi- Cash transfer programs as well as in-kind an amounts between both one adult household transfers are used by countries to alleviate composition types, differences can also be found poverty and hunger while building the human when disaggregating these amounts by institu- capital of future generations. In Malawi, about tion type. For example, in households with one 5 percent of households receive cash from the male adult, median cash transfers from nongov- government and, according to the literature, gov- ernmental institutions13 (MK 30,000) are almost ernment transfers may have positive impacts on twice as high as for their female counterparts the receiver households. For example, Boone et (MK 18,000). But one female adult households al. (2013) find that the Social Cash Transfer Pro- receive higher median amounts in cash from gram, a direct cash transfer from the govern- the government (MK 57,200) than their male ment mainly focused in rural, ultrapoor regions, equivalent (MK 40,000). Although the female resulted in strong increases in time devoted to household type receives higher amounts, of all household farms and in food types consumed one female adult households, only 7.3 percent from own production, as well as in reductions receive cash from the government, whereas 9.4 of ganyu labor, often used as a coping mecha- percent of one male adult households receive nism once food stores have been depleted. Al- these kinds of transfers. though nonconditional cash transfers have been 13 Development partners, nongovernmental organizations, and so on. 37 Poverty and Gender in Malawi successful in reducing poverty and increasing seeds, to improve productivity. Although such schooling, there is no conclusive evidence on the programs have not had positive outcomes in all impact of such transfers on important matters in Sub-Saharan African countries where they were Malawi—such as early marriage and pregnancy implemented (because of misallocation, market among youth (Dake et al. 2018). In contrast, one distortions, and so on), the Malawian case was study finds evidence that women in Malawi who massive in scale and had positive outcomes, in- received monthly cash transfers were less like- cluding improved productivity and increased food ly than others to become infected with HIV or availability. Such transfers and outcomes can herpes (Baird et al. 2012). In addition, Creti and be important facilitators of poverty reduction. Jaspars (2006) argue that cash can improve the Karamba and Winters (2015) find that the Farm status of women and marginalized groups. Input Subsidy led to improvements in agricultural Interestingly, one male adult households productivity for both male and female farmers; seem to receive a higher median amount than however, the program did not provide dispropor- one female adult households in work-related tionate help to female famers overcome gender transfers and programs. For example, they re- disparities in agricultural productivity. Therefore, ceive higher median amounts in Malawi Social because the program offered farm inputs, Karam- Action Fund and in Cash for Work programs. ba and Winters conclude that female farmers These interventions provide employment to un- face additional constraints to productivity apart skilled and semiskilled workers on labor-inten- from nonlabor input use. According to the latest sive projects such as rehabilitation of irrigation data available, about 10.4 percent of one female systems, soil conservation, and road construc- adult households receive vouchers or coupons tion and maintenance. In addition, a higher for free chitowe fertilizer, free urea fertilizer, free share of one male adult households (17.9 per- maize seeds, or free flexi seeds, compared to 9.8 cent) receive free maize and they also receive percent of one male adult households. This is rel- bigger amounts (valued at MK 16,000) than one evant support for one female adult households, female adult households (13.9 percent receive because the program has been found to increase free maize, and the median value is MK 8,000). national maize production and productivity, con- Free food is similar in incidence and in amounts tributing to increased food availability, higher between both household compositions. real wages, and wider economic growth and pov- Malawi also has other quite successful trans- erty reduction (Dorward and Chirwa 2011). Both fer programs, such as the Farm Input Subsi- household composition types were able to obtain dy program (Danida 2011). This program offers about the same amount of seed and fertilizers agricultural inputs, like fertilizers and improved with the vouchers they redeemed. Poverty and Gender in Malawi 38 4. Endowments: Essential Inputs to the Formation of Human Capital Following the World Development Report 2012: principles in the Convention on the Elimination of Gender Equality and Development, we consider All Forms of Discrimination against Women (CE- education and health outcomes under the di- DAW) in 1979 and the Program of Action of the mension of endowments. As such, investments 1994 International Conference on Population and in education and health enable women and men Development. At the Fourth World Conference on to realize their potential as productive members Women (Beijing, 1995), women’s education was of society. The development of human capital has emphasized as key to improving women’s par- shown to be key to ending extreme poverty and ticipation in decision-making in society. Women’s building more inclusive societies (Becker 1995). increased education in particular increases their In addition to the instrumental value of accumu- own well-being as well as the well-being of their lating endowments, good health and education children and the societies they live in (Kabeer are also important in and of their own right; and, 2005; Klugman et al 2014; Levine et al. 2008; for women, emphasis has been given to these Vaughan 2010; World Bank 2012). STAYING IN SCHOOL MATTERS—GIRLS AT A DISADVANTAGE Education level highly correlates with poverty A great deal of the literature has examined in Malawi. Whereas 35.5 percent of household returns to schooling. The work on returns to in- heads in the highest quintile have finished sec- vestment in education is based on the human ondary school, only 1.6 percent of those in the capital theory, whereby investments in educa- lowest quintile achieve secondary education. tion increase future productivity (Psacharopou- These numbers are reflected in the average los and Patrinos 2018). Returns are generally years of education of the household head—9.6 highest for primary education, as well as for years for those in the richest quintile and as low the education of women and in countries with as 5.6 years for those in the poorest quintile. the lowest per capita income. Such returns to Poverty and Gender in Malawi 40 schooling provide the opportunity for people to mary schools. Since then, primary completion raise their future incomes and avoid poverty, rates increased from 36.0 percent to 85.0 per- and for societies to reduce inequality. For low-in- cent for girls and from 46.0 percent to 75.7 per- come countries, the overall rate of return is 9.3 cent for boys between 1994 and 2019 (Figure percent for each additional year of schooling. 4.1).1 When it comes to gender and returns to For Sub-Saharan Africa in particular, the rate is schooling, according to estimations by Psach- even higher: 10.5 percent (Psacharopoulos and aropoulos and Patrinos (2018), the private Patrinos 2018). returns to female education exceed those of Although Malawi’s primary school enroll- males by about 2 percentage points. This does ment for both boys and girls has increased in not imply that earnings are higher for females, the past two decades, school completion rates but only that education is a good investment for are low. In 1994, the government of Malawi women and girls, and a development priority banned school fees for publicly financed pri- for reducing poverty. Figure 4.1. Primary school completion rates (% of relevant age group) 100 80 % of relevant age group 60 40 20 0 1990 1995 2000 2005 2010 2015 2020 Year Female Male Source: World Development Indicators (https://datatopics.worldbank.org/world-development-indicators/). Despite the desirability of higher enrollment (for example, repeaters). At the same time, per- rates, gross enrollment rates over 100 percent sistence to grade 5 is higher among girls in 2019 indicate that a significant share of students (73.48 percent for girls versus 69.80 percent for in school are older than the official age group boys). Literacy rates still reflect a gender gap in 1 Data from the World Bank’s World Development Indicators (https://datatopics.worldbank.org/world-development- indicators/). 41 Poverty and Gender in Malawi education, taking into account all age cohorts of cantly higher in Malawi compared to same rate the population; in 2015, 55.2 percent of Malawi- in SSA: 75.8 percent for women in Malawi versus an women ages 15 and above were literate com- 59.8 percent in SSA and 62.1 percent for men in pared to 69.8 percent of men. Malawi versus 53.1 percent in SSA (WDI, 2019). Secondary school enrollment and completion Other challenges for education in Malawi are significantly lower than primary school en- are that a significant proportion of enrolled stu- rollment and completion. The lower secondary dents demonstrate chronic absenteeism and completion rate is significantly lower than the that many drop out of the system altogether. Not average for Sub-Saharan Africa (SSA): 20.5 per- having enough money for uniforms is the first cent for females in Malawi versus 39.05 percent reason for primary education dropout, followed for SSA, with latest available data (2013) and by lack of interest (Figure 4.2). Girls are dispro- 22.7 for males in Malawi versus 44.8 percent portionally affected by marriage and pregnan- in SSA (2013). In fact, the rate of out-of-school cy:2 only 2.1 percent of boys drop out for these youth of upper-secondary school age is signifi- reasons, whereas 16.1 of girls do so. Figure 4.2. Reasons for dropping out of primary education 75 Percent dropping out, by reason 61 60 55 45 30 22 16 16 15 2 3 3 2 2 2 1 4 3 1 1 0 No money for fees or uniform Not interested, lazy Married / became pregnant Illness or disability Too old to continue Had to work or help at home Parents told me to stop Other Male Female Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. Staying in school is essential for young girls percent of boys of lower secondary school age and boys, but about 18 percent of girls and 19 are out of school. This is an important con- 2 “Marriage and pregnancy” is one of the listed options in the questionnaire both for men and for women. Poverty and Gender in Malawi 42 cern and has not significantly improved over ularly high level, resulting in a prevalence rate time: in 2009, the share of adolescents out of of child marriage of 10 points above the region- school was 21 percent for girls and 19 percent al average (World Bank 2018c). The same report for boys. Regarding dropout in secondary edu- finds a clear relationship between educational cation, an even higher proportion of girls drop attainment and child marriage: the higher the out of school because of marriage and teen- child marriage rate, the lower girls’ education- age pregnancy (Figure 4.3). Again, the gender al attainment. In addition, among all girls aged gap is very wide: 3.9 percent for men versus 15–19, only 1.5 percent are married and attend 26.9 for women. Among comparable countries school and 25.2 percent are married and do such as Mozambique, Tanzania, and Zambia, not attend school. The remaining 73.3 percent the prevalence of child marriage decreased by is composed of girls not married and in school 7.6 percentage points over the last two and a (52.7 percent) and girls not married and out half decades, meaning that child marriage is of school (20.6 percent). Therefore, child mar- 7.6 percentage points lower for women aged riage, which also strongly correlates with early 18–22 than for women aged 41–49. For Malawi, childbearing, has a strong impact on girl’s edu- the decrease in child marriage was similar (7.4 cational attainment, being the main reasons for percentage points), but it started from a partic- girls’ dropout (World Bank 2018c). Figure 4.3. Reasons for dropping out of secondary education 80 Percent dropping out, by reason 71 70 58 60 50 40 26 30 20 6 5 7 10 3 3 3 2 1 1 0 1 1 1 1 0 0 No money for fees or uniform Married / became pregnant Not interested, lazy Acquired all education wanted Found work Failed promotion exam Illness or disability Too old to continue Other Male Female Source: Calculations based on Malawi’s Fifth Integrated Household Survey, 2019–20. The 2014 School to Work Transition Survey young people aged 15–29 years. In particular, it (SWTS) generates labor market information on looks in detail at transitions from school to work 43 Poverty and Gender in Malawi and, consequently, collects relevant information they got married. On the contrary, only 7.1 percent on education and dropouts. Similar to the results of men dropped out because of marriage. This found in IHS data, data from the SWTS show that reason for dropping out is more frequent among women are disproportionally affected by marriage girls ending education during primary education when it comes to education. In fact, 24.4 percent of (29.3 percent) than among girls ending their edu- women who dropped out of school did so because cation while in university (23.7 percent).3 REPRODUCTIVE HEALTH Human capital investments (health and educa- es that include high rates of maternal and in- tion) affect the outcomes of women and men fant mortality, fertility, teenage pregnancy, and throughout the course of their lives, including high HIV prevalence. Although high, Malawi’s their agency within the family and community, 2017 maternal mortality ratio of 349 deaths per and such investments also provide important 100,000 live births was substantially below SSA foundations for women’s access to economic average of 534 deaths per 100,000 live births opportunities. Yet in Malawi, like in many SSA and has decreased at a higher pace than the re- countries, women face several health challeng- gion’s average since the 2000s (Figure 4.4). Figure 4.4. Maternal mortality ratio, 2000–17 1000 per 100,000 live births (modeled estimate) 500 0 2000 2005 2010 2015 Year Malawi Sub-Saharan Africa Source: World Development Indicators (https://datatopics.worldbank.org/world-development-indicators/). Note: Figure shows a modeled estimate. 3 No data on secondary dropout were shown because the survey collected data on only 21 girls dropping out during secondary education. If one considers these data reliable despite the small observation number, one could argue that marriage is particularly important during secondary education, because 50 percent of those dropping out during this level do it because of marriage. Poverty and Gender in Malawi 44 Factors driving high rates of maternal mor- SSA average is 0.98 nurses and midwives per tality include hemorrhage, infection, unsafe 1,000 population. abortion, pre-eclampsia/eclampsia, and ob- The share of women receiving prenatal care structed labor; indirect causes include malar- has risen to 97.6 percent6 (WDI, 2017), significant- ia, anemia, HIV/AIDS, and tuberculosis (WHO ly above the 81.91 percent for SSA7 on average. 2015). Most maternal deaths are considered While the share of births taking place in health preventable, yet they persist in Malawi be- facilities has risen to an estimated 89 percent,8 cause of the combination of a high total fer- overcrowding of facilities and systemic health tility rate and limited access to contraception, system failures have limited Malawi’s ability to weak health infrastructure, shortages of health capitalize on this impressive trend (Colbourn et professionals, and low institutional capacity al. 2013; Mgawadere et al. 2017). Nevertheless, (Bazile et al. 2015; WHO 2015).4 Furthermore, Malawi’s infant mortality rate has fallen over the human resources for maternal health are last decade (Figure 4.5). Particularly, the country limited with only 0.43 nurses and midwives shows lower rates than its neighboring countries, per 1,000 population.5 As a comparison, the Tanzania, Mozambique and Zambia. Figure 4.5. Infant mortality ratio, 1990–2018 160 per 1,000 live births 80 0 1990 1995 2000 2005 2010 2015 Year Malawi Sub-Saharan Africa Source: World Development Indicators (https://datatopics.worldbank.org/world-development-indicators/). 4 A study at a large facility in Malawi indicates that 24 percent of maternal deaths in 1999 were attributable to postabor- tion complications (Lema, Changole, and Kanyighe 2005). 5 World Development Indicators, 2018 (latest available data). 6 World Development Indicators, 2017 (latest available data). 7 World Development Indicators, 2016 (latest available data). 8 World Development Indicators, 2016 (latest available data). 45 Poverty and Gender in Malawi Along with its great progress over the last alence populations has been observed since an- few decades in terms of infant and maternal tiretroviral therapy scale-up (Price et al. 2016). mortality, Malawi has also made improvements In addition, as noted previously, infant mortali- in life expectancy. Life expectancy has increased ty rates decreased far beyond the SSA average from 48 years for women and 44 years for men from 1990 to 2018, and maternal mortality rates in 1990 to 67 and 61 years in 2018, respective- have been reduced by more than half, decreas- ly (Figure 4.6). Indeed, since the HIV outbreak in ing from 749 deaths per 100,000 live births in 1985, improved life expectancy in high HIV prev- 2000 to 349 in 2017. Figure 4.6. Life expectancy at birth 70 Life expectancy (years) 45 20 1990 1995 2000 2005 2010 2015 Year Female Male Source: World Development Indicators (https://datatopics.worldbank.org/world-development-indicators/). Of concern, however, are data from the latest given its physical, psychological, and socioeco- Malawi Demographic and Health Survey (2015– nomic consequences on the teenage mother, 16), which show in an increase in the share of family, and society. The risk of maternal mortali- teenage girls (aged 15 to 19) bearing children. ty is higher for adolescent girls, especially those That share is 29 percent,9 4 percentage points under age 15, compared to older women (Nove higher than the share recorded in the 2010 De- et al. 2014). Research on the topic has shown mographic and Health Survey. Teenage preg- the many different consequences on the mother nancy is a health and social problem in Malawi and the child, suggesting that teenage pregnan- 9 A recent study in the Zomba district of Malawi found that early sex and marriage, low contraceptive use, low education- al levels, low socio-economic status, lack of knowledge of reproductive and sexual health, gender inequity, and physi- cal/sexual violence were the most prominent factors associated with the high levels of unplanned teenage pregnancy (Kaphagawani and Kalipeni 2017). Poverty and Gender in Malawi 46 cy compromises women’s educational, social, traceptive use by currently married women has and economic prospects (see UNFPA 2013 for increased steadily during the last 25 years, it re- an overview; Azevedo et al. 2012; Kruger and mains low among 15-to-19-year-old girls (Figure Berthelon 2012). .In addition, the effects of teen- 4.7 and Figure 4.8). Only 15.2 percent of adoles- age pregnancy are not limited to the mothers. cent girls aged 15–19 use a modern contraceptive Children of adolescent mothers are also likely to method (Figure 4.8). Unmet need for contracep- face lower educational outcomes and to engage tion is high at 19 percent for women aged 15–49 in risky behavior (Azevedo et al. 2012; Hoffman and at 22 percent for adolescent girls aged 15- 2008). Beyond its impact on individuals, teenage 19.10 Health concerns or fear of side effects are pregnancy is also important in the context of the the predominant reasons women do not intend to discussion on population dynamics and wom- use modern contraceptives in future (cited by 26 en’s fertility, both issues of global relevance. percent of those not intending to use them). Cost Contraceptive prevalence in Malawi is above and access are lesser concerns, indicating further SSA levels—59.2 percent in Malawi (2016) versus need to strengthen demand for family planning 31.2 percent in SSA (2017). Although modern con- services and thereby the effectiveness of those. Figure 4.7. Percentage of currently Figure 4.8. Use of modern married women using a contraceptive contraception method, method, 1992-2016 by age group % of women using contraception, 70 59 59 % of currently married women using 60 56 52 46 45 43 by age group contraception 35 30 15 0 1992 2000 2004 2010 2015/16 Year 0 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Total Any modern method Any traditional method Age group Source: Malawi Demographic and Health Survey 2015–16 Report. The 2015–16 Malawi Demographic and age, men in Malawi initiate sexual intercourse at Health Survey also points to relatively early ini- slightly older ages than women. The median age tiation of sex among Malawian youth. On aver- at first sexual intercourse reported by people 10 Data in this paragraph come from the Malawi Demographic and Health Survey 2015–16. 47 Poverty and Gender in Malawi aged 25–49 is 16.8 years for women and 18.5 cent had first sex before age 15, and 64 percent years for men. Of women aged 25–49, 19 per- before age 18. DISPROPORTIONATE EFFECT OF HIV-AIDS ON WOMEN IN MALAWI Malawi has one of the highest HIV preva- duce the HIV epidemic have been made at both lence rates in the world, with 8.9 percent of the national and local levels. In 2019, 90 percent of adult population (aged 15–49) living with HIV people living with HIV in Malawi were aware of (UNAIDS 2019). An estimated 1.1 million Mala- their status; 79 percent of those aware were wians were living with HIV in 2019, and 13,000 on treatment, and 72 percent of those on treat- Malawians died from AIDS-related illnesses in ment were virally suppressed. Furthermore, the same year (UNAIDS 2019; Figure 4.9 to Fig- new infections have dramatically declined from ure 4.12). Nevertheless, AIDS-related deaths 74,000 new infections in 2005, to 33,000 in 2019 diminished by 59 percent between 2010 and (UNAIDS 2019; Figure 4.9). Malawi has also 2019. The Malawian HIV epidemic plays a crit- witnessed a reduction in HIV infections among ical role in the country’s low life expectancy of children. There were 4,300 new pediatric infec- just 60.7 years for men and 66.9 for women.11 tions in 2016, compared with 16,000 in 2010 Over the last decade, impressive efforts to re- (UNAIDS 2019). Figure 4.9. New HIV infections, Figure 4.10. People living with AIDS, 2005–19 2005–19 80000 1200000 65000 People living with HIV New HIV infections 400000 40000 600000 74000 2500 1000000 59000 950000 970000 13000 600000 36000 17000 0 0 2005 2010 2016 2019 2005 2010 2016 2019 Year Year All ages Women (15+) Men (15+) Children (0-14) All ages Women (15+) Men (15+) Children (0-14) 11 World Development Indicators, 2019. Poverty and Gender in Malawi 48 Figure 4.11. AIDS-related deaths, Figure 4.12. HIV incidence, 2005–19 2005–19 HIV incidence per 1000 population 80000 7 6 AIDS- related deaths 4 3 40000 3,5 73000 2 45000 1 1900 24000 5600 0 5400 2005 2010 2016 2019 0 All ages All ages All ages All ages Adults Year (14-49) 2005 2010 2016 2019 All ages Women (15+) Men (15+) Children (0-14) Year Source: UNAIDS 2019. HIV disproportionately affects women in Mala- high HIV prevalence include early sexual activity wi. A national assessment of the impact of HIV on and sexual assault and abuse.12 Women’s subor- the population, carried out by the Malawian Min- dinate position in Malawian society and harmful istry of Health in 2015–16, found HIV prevalence cultural practices that promote ritual and casu- among adult women (aged 15–64) to be 13 per- al sexual intercourse, initiation practices, and cent, compared with 8 percent among adult men sexual abuse render women more vulnerable (Ministry of Health 2016). This disparity is espe- to HIV infection. cially prominent among 25-to-29-year-olds: HIV The knowledge-behavior gap regarding con- prevalence is three times higher among women dom use for HIV prevention has narrowed in the than men in this age group (14 percent versus 5 past 15 years (Figure 4.13). Although about 75 percent) (Ministry of Health 2016). Unprotected percent of women and men aged 15–49 know heterosexual sex between married or cohabiting that using condoms consistently can reduce partners accounts for 67 percent of all new HIV the risk of HIV, currently 50 percent of women infections, whereas unprotected casual hetero- and 76 percent of men report having used a sexual sex accounts for 12 percent (NAC 2015). condom at last higher-risk intercourse with a Beyond this, several population groups such as nonmarital, noncohabiting partner.13 Over time, adolescent girls and young women, sex workers, men have closed this knowledge-behavior gap and men who have sex with men are particularly more successfully than women have: the gap is vulnerable to HIV. Other factors that contribute to nonexistent for men, but there is still a 25-per- 12 From Avert’s “HIV and AIDS in Malawi” web page (https://www.avert.org/professionals/hiv-around-world/sub- saharan-africa/Malawi). 13 Malawi Demographic and Health Survey 2015–16. 49 Poverty and Gender in Malawi centage-point gap for women. This means that, using condoms, not all have the access, will, or although women are aware of the advantages of ability to protect themselves. Figure 4.13. Knowledge-behavior gap regarding use of condoms, 2000–16 100 Percent reporting or condom use knowledge 50 0 2000 2004 2010 2015/16 Year Women - Condom use at last higher sex (with a nonmarital, noncohabiting partner) Men - Condom use at last higher sex (with a nonmarital, noncohabiting partner) Women - Knowledge of HIV prevention methos, use of condomns Men - Knowledge of HIV prevention methos, use of condomns Source: Malawi Demographic and Health Survey (DHS), Stat compiler (https://www.statcompiler.com/en/: ). Note: Condom use at last higher-risk sex: Percent of men and women who say they used a condom the last time they had sex with a nonmarital, noncohabiting partner, of those who have had sex with such a partner in the last 12 months. Knowledge of HIV prevention methods - Use of condoms: percentage who, in response to a prompted question, say that people can protect themselves from contracting HIV by using condoms. Poverty and Gender in Malawi 50 5. Women’s Agency: A Crucial Driver behind Outcomes of Well-Being Agency is the capacity to make decisions about development dividends for them and for their one’s own life and to act on them to achieve de- families, communities, and societies. By con- sired outcomes. Increasing women’s agency trast, constraining women’s agency will result in is important and valuable in and of itself. But productivity losses for economies, societies, and agency also has instrumental value: amplifying communities. Women’s agency is fundamental the agency of women and girls can yield broad to end poverty and boost shared prosperity. LEGAL CONTEXT Malawi’s Constitution recognizes women’s right lawi scores 77.5 out of 100 on this index, which to full and equal protection under the law and is higher than the regional average observed to nondiscrimination based on gender or marital across Sub-Saharan Africa (71). The index is status.1 Furthermore, the Malawian government based on 35 questions scored across eight in- has developed laws, policies, and programs that dicators; overall scores are then calculated by promote protection and respect for women’s and taking the average of each indicator, with 100 girls’ human rights.2 The World Bank’s Women, representing the highest possible score.4 When Business and the Law database3 presents an in- it comes to laws affecting women’s decisions to dex covering 190 economies and is structured work, laws affecting women’s pay, constraints around the life cycle of a working woman; Ma- related to marriage, and gender differences in 1 Malawi Constitution, art. 24. Discrimination on the basis of sex is also prohibited in art. 20 (1). 2 Malawi adopted the Gender Equality Act 2013, the Deceased Estates (Wills, Inheritance and Protection) Act 2011, the Child Care Protection and Justice Act 2010, and the Legal Aid Act 2010. 3 For more on Women, Business and the Law, see https://wbl.worldbank.org/en/wbl. 4 Data refer to the laws and regulations that are applicable to the main business city (Blantyre). Different rules may apply in other jurisdictions, so local legislation should be reviewed. Poverty and Gender in Malawi 52 property and inheritance,5 Malawi gets a full some struggle. As highlighted in a recent qual- score. However, when it comes to constraints on itative study (Muller et al. 2019), weaknesses freedom of movement, laws affecting women’s of local institutions in enforcing gender-related work after having children, constraints on wom- legislation prevent many women from access- en’s starting and running a business, and laws ing justice. However, specific local circumstanc- affecting the size of a woman’s pension, Malawi es should be considered, given that Malawi’s should consider reforms to improve legal equal- Local Government Act provides for District ity for women. For example, one of the lowest Assemblies to formulate bylaws for the local scores for Malawi is on the indicator related to jurisdiction. Bylaws include those on child mar- laws affecting women’s work after having chil- riage, gender-based violence, harmful cultural dren (see appendix C for an overview of legis- practices, and the need for girls to go to school. lation considered for the Women, Business and The Gender Empowerment Network in Malawi the Law 2021 database). worked with traditional leaders in Chiradzulu It is important to emphasize, though, that District, for example, to develop local bylaws consultations with local stakeholders stress prohibiting child marriage. Men who engaged the distinction between de jure and de facto law in the practice were fined in goats and chick- with regard to women’s rights: although laws ens. This significantly reduced child marriage may on paper protect women’s rights in Malawi, in the area and improved school enrollment access to justice for women may be a burden- (GENET 2013). VIOLENCE AGAINST WOMEN AND GIRLS—A NEGATION OF THEIR HUMAN RIGHTS “The issue is poverty. . . . We have no job, no business, so we depend on selling our bodies to get money.” Woman from affected community, 25–35 years old, Southern region (cited in Muller et al. 2019) A recent qualitative study on how the influx of munities showcases the deep interconnection labor for infrastructure projects affects the hu- between women’s agency, their exposure to vio- man rights of women and girls in poor host com- lence, and poverty (Muller et al. 2018). One of the 5 Although both matrilineal and patrilineal systems operate in Malawi’s ethnic groups, both perpetuate discrimination against women in the family (Kamyongolo and Malunga 2011). For example, wives are often victims of discriminatory inheritance practices in which the deceased husband’s family unlawfully takes property. 53 Poverty and Gender in Malawi main conclusions of this study is that the influx other woman, an occurrence that participants of outsiders not only causes many of the harm- attributed to the practice of polygamy. ful observed effects but also essentially worsens Violence against women in Malawi appears existing deep imbalances in gender dynamics widespread. Data from the 2015–16 Malawi of power and influence within the communities. Demographic and Health Survey show that 34 Preexisting social issues, institutions, and cultur- percent and 21 percent of women have experi- al norms and the persistent poverty in rural com- enced physical violence and sexual violence, re- munities shape the negative outcomes observed spectively, since age 15, with rates of sexual and in the context of those infrastructure projects. physical intimate partner violence varying by age According to the same study, poverty and and peaking for the 25-to-29-year-old age group economic necessity are major drivers leading (Figure 5.1 and Figure 5.2). Prevalence rates are women and girls to enter abusive relationships. higher in rural areas than in urban areas. Many The limited means that women and girls have women have experienced controlling behaviors to provide for themselves and bring change to from a husband or intimate partner, such as in- their lives are at the center of motivations for sisting on knowing where they are at all times getting involved in abusive relationships. Wom- (60 percent), being jealous or angry if they talk en interviewed for this study depended on men to other men (50 percent), accusing them of be- in their households for support. Particularly in ing unfaithful (24 percent), not permitting them the Northern region, research participants said to meet their female friends (13 percent), and it was common for a man to stop providing for limiting their contact with their families (11 per- his family after initiating a relationship with an- cent) (NSO 2017, 283). Figure 5.1. Women’s experience of physical and sexual violence, 2004–16 40 Percent who experienced violence 34 28 28 25 21 20 16 13 14 14 14 11 12 0 Ever experienced Physical violence in Ever experienced Sexual violence in physical violence the past 12 months sexual violence the past 12 months since age 15 (ages often or sometimes (ages 15-49) (ages 15-49) 15-49) (ages 15-49) 2004 2010 2015/16 Source: Malawi Demographic and Health Survey (DHS), 2004, 2010, 2015–16. Poverty and Gender in Malawi 54 Figure 5.2. Women’s experience of physical and sexual violence in the last 12 months by age groups 25 22 20 19 Percent who experienced violence in the 17 16 16 15 15 14 14 14 14 13 13 past 12 months 11 10 8 5 0 Physical violence in the past 12 months Sexual violence in the past 12 months often or sometimes (ages 15-49) (ages 15-49) 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Source: Malawi Demographic and Health Survey 2004, 2010, 2015–16. A 2012 study looking at domestic violence out without telling him, she neglects the children, against pregnant women at a district hospital in or she refuses to have sex with him (Figure 5.3 southern Malawi finds that 59 percent had been and Figure 5.4). Attitudes toward wife beating do psychologically, physically, or sexually abused not appear to have changed since the 2010 De- during pregnancy (Chasweka et al. 2012). In mographic and Health Survey. For both women terms of attitudes toward intimate partner vi- and men, there is a 2-percentage-point or less olence, the Malawi Demographic and Health change in attitudes during this time. However, as Survey 2015–16 also shows that 16 percent of Beegle et al. (2018) show, women’s acceptance women and 13 percent of men said the husband of domestic violence varies widely across coun- is justified in hitting or beating his wife if at least tries in Africa: of the more than 30 Sub-Saharan one of the following five circumstances occurs: African countries included in the review, Malawi she burns the food, she argues with him, she goes scored the lowest in acceptance rates. 55 Poverty and Gender in Malawi Figure 5.3. Malawian women who believe a husband is justified in beating his wife, by income quintile 40 38 37 husband is justified in beating his wife 40 35 Percent of women who believe a 31 32 30 30 26 19 18 20 18 17 17 14 15 14 13 13 12 13 11 10 10 9 0 Q1 Q2 Q3 Q4 Q5 Expenditure quintiles 2000 2004 2010 2014 2016 Source: Malawi Demographic and Health Survey, Stat compiler (https://www.statcompiler.com/en/: ). Note: Figure shows women’s responses to whether a husband is justified in beating his wife for any of the following five reasons: she burns the food, she argues with him, she goes out without telling him, she neglects the children, or she refuses to have sex with him. Figure 5.4. Malawian women who believe a husband is justified in beating his wife, by reason for beating She neglects the children 8 She refuses to have sex with him 8 She goes out without telling him 6 She argues with him 6 She burns the food 5 0 2 4 6 8 10 Percent of women who believe a husband is justified in beating his wife Source: Malawi Demographic and Health Survey, 2015–16, Stat compiler (https://www.statcompiler.com/en/: ). Poverty and Gender in Malawi 56 The literature also indicates a number of pleasing one’s husband as well as being harmful traditional practices that constitute gentle and obedient wives. The initiation at gender-based violence or that put women and times involves bringing in a man, common- girls at risk for gender-based violence (Bisika ly known as a fisi (hyena in English), who is 2008; Kamyongolo and Malunga 2011; Lomba expected to have sexual intercourse with the 2014; Malawi Human Rights Commission 2005; girl to test the knowledge she has gained. The NSO 2012): fisi is usually chosen by the community, and the sexual intercourse is condoned, even wi- • Property grabbing. When a man dies, the thout the girl’s consent, because it is sanctio- property is taken away from the communi- ned by the community. ty members and widow and children by the relatives of the deceased. As more and more • Ritual cleansing ceremonies. Certain rituals people die of AIDS, property grabbing is now demand sexual intercourse with women as a common practice in both rural and urban a form of cleansing and to appease spirits Malawi. when calamity has befallen a community or as prevention of calamity. Women must the- • Wife inheritance. When the husband dies, the refore participate in these rituals whether or widow is forced to marry one of husband’s not they approve of the person the communi- relatives, as if she were an object of posses- ty chooses for them to have sex with. One of sion to be transferred. those rituals is known as widow cleansing. In • Polygamy. The practice of having multiple wi- widow cleansing, a man known as a fisi (the ves. According to the Malawi Demographic same meaning noted previously for initiation and Health Survey 2015–16,13 percent of ceremonies) has sexual intercourse with a currently married women reported that their woman whose husband has died in order to husband has more than one wife. Although appease the spirit of the dead husband. Ano- polygamy is prohibited by the Malawian Pe- ther ritual of the same type happens when a nal Code for common law marriages and is household purchases an important item such similarly prohibited in the Marriage, Divorce as a canoe for business or when a family and Family Relations Bill passed by Parlia- wants to burn bricks for building a house. A ment in 2015, customary laws allow for this fisi is called upon to have sexual intercourse type of marriage and efforts to outlaw poly- with a woman in the family to appease spirits gamy have met with strong opposition from so that the business will thrive or the bricks religious leaders (CEDAW 2013). will burn well. • Initiation ceremony. In most Malawian com- • Installation of new chiefs (“Kulandira Alen- munities, when a girl reaches puberty, she do”). This is another commonly practiced undergoes an initiation ceremony welcoming rite among the Chewa tribes of the Central her into adulthood. Girls are taught about Region of Malawi that violates the rights of 57 Poverty and Gender in Malawi young girls. During the installation of new • Female genital mutilation (FGM). Traditional chiefs, other chiefs from near and far come chiefs in parts of Malawi have confirmed that and spend nights in the chief designate’s vi- FGM is prevalent (Chatora 2015), but there is llage. During such nights, part of traditional limited information on the prevalence of FGM etiquette requires organizing young girls who in Malawi (Malawi Human Rights Commis- will be required to keep the visiting chiefs sion 2005). CEDAW (2015) expresses concern company and have sex with them during the regarding the existence of FGM or cutting in night. Like in most cultural rites, the girls in- some regions of the country. The US Depart- volved are never consulted for their express ment of State (2017) reports that there is no opinions about the arrangement. specific legislation prohibiting FGM. CHILD MARRIAGE—A SPECIFIC FORM OF VIOLENCE AGAINST WOMEN THAT LIMITS GIRLS’ PROSPECTS IN MULTIPLE DIMENSIONS OF WELL-BEING Malawi has among the highest rates of child mar- tion in society but stigmatize adolescent pregnan- riage in the world. On average, 1 in 10 girls is cy. Marriage is regarded as a means of protecting married by age 15 and 4 in 10 girls are married girls who get pregnant from undermining family by age 18 (Table 5.1). Data show little to no change honor (Human Rights Watch 2014). in child marriage prevalence since 2000. Child In February 2017, Parliament amended the marriage is common across all three regions of Constitution and raised the age of marriage Malawi, and in both rural and urban areas. An in- from 15 (with parental consent) to 18 years old depth qualitative study by Human Rights Watch for boys and girls. The president signed the con- (2014) in six districts in Central and Southern Ma- stitutional amendment into law at the end of lawi, finds that the most important reasons for April 2017. The move brings the Constitution in the prevalence of child marriage in Malawi are line with the Marriage, Divorce and Family Re- poverty, lack of adequate education, employment lations Bill developed in 2006 that has stronger opportunities, teenage pregnancy, traditions, and protections against child and forced marriage patriarchal cultures that encourage early sexual and provides 18 as the minimum marriage age initiation and marriage and women’s subordina- (Girls Not Brides 2017). Poverty and Gender in Malawi 58 Table 5.1. Rates of child marriage, by gender Girls Boys Married by age 15 Married by age 18 Married by age 15 Married by age 18 Survey (%) (%) (%) (%) 2015–16 DHS 9.0 42.1 0.0 6.5 2010 DHS 11.7 49.6 1.2 6.4 2004 DHS 10.7 48.9 0.1 7.8 2000 DHS 10.2 46.9 0.8 4.8 1992 DHS 14.8 54.9 1.3 4.8 Source: Malawi Demographic and Health Survey (DHS), Stat compiler (https://www.statcompiler.com/en/: ). Note: To assess the prevalence of child marriage, this analysis used Sustainable Development Goal indicator 5.3.1, the percentage of women aged 20 to 24 years who were first married or in union before age 18. All references to “marriage” include both formal marriages and informal unions in which women started living with a partner as if married. Child marriage has negative impacts on many child brides remained financially depen- poverty as well as important impacts on girls’ dent on often abusive spouses in part because health, education, and exposure to physical, they lacked the education and skills needed to mental, and sexual violence. A recent global provide for themselves and their families. study—comprising 25 countries that account for The study documents cases in which child an overwhelming majority of child marriages marriage exposed girls to gender-based vio- worldwide—finds that child marriage has a wide lence, including domestic and sexual violence. range of large negative impacts on girls, their Some girls who rejected forced marriages children, families, communities, national societ- said they were threatened, verbally abused, or ies, and, through a variety of costs, economies thrown out of their homes by their families (Hu- at large (Wodon et al. 2017). In Malawi, inter- man Rights Watch 2014). Other girls reported views with young women as part of the Human that their husbands abandoned them and left Rights Watch qualitative study (2014) reveal that them to care for children without any financial marriage interrupted or ended their education. support, thus increasing the likelihood of their Many said that they found it difficult to return to being impoverished. The study also documents school after marriage because of lack of money cases in which child marriage led girls into for school fees, lack of childcare, unavailability commercial sexual exploitation and child la- of flexible school programs or adult classes, and bor. Health workers interviewed as part of the the need to do household chores. Others said that study described the reproductive health harms their husbands or in-laws would not allow them and risks of early pregnancy when girls marry to continue school after marriage. In adulthood, young, including maternal death, obstetric fis- 59 Poverty and Gender in Malawi tula, premature delivery, and anemia (Human force participation through its impacts on girl’s Rights Watch 2014). educational attainment and total fertility (World Another study, the “Malawi Economic Moni- Bank 2018c). It also argues eliminating child tor: Investing in Girl’s Education,” argues that the marriage could have significant impact on earn- elimination of child marriage could affect labor ings and productivity of girls and women. WOMEN’S LIMITED DECISION-MAKING IN PRIVATE AND PUBLIC SPHERES Although women’s autonomy has increased in husband in 2016. This compares to the 71 per- the last 15 years, it remains low compared to cent who in 2000 responded that decisions on that of men. Women’s agency is highly relevant women’s health care were made mainly by her not only for women’s autonomy, but also be- husband. In 2016, decisions concerning major cause it affects their ability to build human cap- household purchases were made primarily by ital and take up economic opportunities. Figure husbands (44 percent) or jointly (47 percent). 5.5 shows women’s participation in household This compares to 81 percent of ever-married decision-making, with the percentage of wom- women who responded in 2000 that decisions en who report that specific household decisions on household purchases were made primarily are made by their husbands, by themselves, by their husbands. When it comes to decisions or jointly with their husbands. Of the total re- about a woman’s visit to her family and rela- spondents, 19 percent of ever-married women tives, women still have little autonomy, with only made decisions on their own health care alone 18 percent reporting that they make these deci- and 40 percent made decisions jointly with their sions by themselves. Poverty and Gender in Malawi 60 Figure 5.5. Percentage of currently married women aged 15-49 participation in household decision-making 81 71 (age 15 -49) indicating decision-maker Percent of currently married women 61 49 47 45 44 36 32 21 19 21 19 18 12 8 7 9 Mainly Mainly Both Mainly Mainly Both Mainly Mainly Both husband wife husband wife husband wife Decision maker about a Decision maker about a Decision maker about major woman's visits to her family woman's own health care household purchases or relatives 2000 2016 Source: World Development Indicators (https://datatopics.worldbank.org/world-development-indicators/). Some interesting trends with regard to de- of the husband is seen to decline, and the share cision-making should be noted. In terms of of respondents indicating joint decision-making women’s health, whereas the husband was the between husband and wife increases. predominant decision-maker in 2010, this status When it comes to public decision-making had declined by 2016. This change is not because and political representation, few women hold women themselves have taking on more deci- decision-making positions within Malawi’s sion-making capacity, but instead because a large social, political, and economic arenas. Wom- increase can be seen in joint decision-making. The en are underrepresented at most levels of same patterns can be observed when it comes to government, including in ministerial bodies decision-making around a woman’s visits to her and parliament. As of 2020, women hold only family or relatives and to major household pur- 22.9 percent of all seats in parliament. Malawi chases: the predominant decision-making power has no legislated quotas to promote women’s 61 Poverty and Gender in Malawi political participation, although several political ties aim to have filled by women, either at the parties have adopted voluntary quotas ranging parliamentary level or at all levels of the party from 25 to 33 percent of seats, which the par- structure (Quota Project 2013).6 6 Attitudes toward women as leaders may play a role in the level of women’s political voice in Malawi. A 2008 study sug- gests that Malawians associate politics with “male” traits of strength, deceit, and fighting (Kamlongera 2008). Women’s own attitudes also play a role: female politicians themselves have reported that women are incapable of evaluating political issues. The study reports that single female politicians are particularly regarded with suspicion and that, generally, female politicians face discrimination in campaigning. With respect to women’s participation in civil society, in 2010 the government reported that there is a poor representation of women in civil society leadership positions. For example, women held only 274 head of community organization positions, compared to 1,603 positions held by men (NSO 2010). Poverty and Gender in Malawi 62 6. In Closing Malawi has seen important improvements in sev- likelier than men to be poor during core produc- eral key development outcomes and a narrowing tive and reproductive stages of life. Furthermore, of gender gaps over the past several decades. households composed of only one female adult Life expectancy has increased significantly over with children are the poorest among all house- the last 30 years, likely due in part to antiretro- hold compositions. Relatedly, households with viral therapy scale-up (Price et al. 2016). In addi- children are consistently poorer, and the more tion, infant mortality rates decreased far beyond children a household has the higher its probabili- the Sub-Saharan Africa average between 1990 ty of being poor. In this context, the conjunction of and 2018, and maternal mortality rates have high fertility and poverty becomes relevant. been reduced by more than half since 2000. Also, Two customary systems—matrilineal and Malawi experienced a steep drop in fertility from patrilineal—can be distinguished in Malawi. 6.7 births per woman in 1990 to 4.1 in 2018, de- Under the patrilineal system, land is trans- creasing much faster than the regional average. ferred from fathers to sons and power and de- Likewise, Malawi has made enormous strides in cision-making capacity are assigned to men education. Since the 1994 ban on school fees for rather than women. The matrilineal system publicly financed primary schools, primary com- works in the opposite way. In theory, women are pletion rates increased from 36 to 85 percent for supposed to be the main decision-makers and girls, and from 46 to 76 percent for boys. landowners; however, in practice, women do not Despite those improvements, the latest benefit as much under this system as men do household survey for Malawi (the Fifth Integrat- under the patrilineal system. For example, agri- ed Household Survey [IHS5], 2019–20) confirms cultural female-managed households under the a large gender disparity in poverty rates, with patrilineal system are 5 percentage points more women more likely to be poor—especially if they likely to be poor than male-managed house- are single mothers and during the core productive holds, and they are still more likely to be poor stages of life. Malawian women are more likely under the matrilineal system. Also, female land- than men to live in poor households starting in owners are less likely than male landowners to their mid-20s through their 50s; hence, they are make decisions about their land. 64 Poverty and Gender in Malawi Gender disparities vary significantly across Key to thinking about how to break the cycle regions of the country, suggesting that a target- of chronic and women-biased poverty is recog- ed spatial approach may be effective in address- nizing gender disparities in underlying drivers of ing the gender disparities that drive poverty. poverty that perpetuate disadvantages for wom- The main regions in Malawi—Central, Northern, en. Most critical of these drivers are the following. and Southern—are economically and culturally quite distinct. Malawi’s rural Northern region • Women’s access to economic opportunities is mainly patrilineal (95.2 percent of persons and the ability to generate an income—one of there report living under the patrilineal tradi- the main pathways out of poverty—is limited. tion), whereas the rural Southern region has a Although female labor force participation ra- stronger presence of the matrilineal system tes are relatively high, the quality of women’s (63.3 percent of people living there report hav- participation in the labor force is below that of ing married under the matrilineal tradition, ac- their male counterparts: women work fewer cording to the IHS5). Urban areas as well as the hours of wage employment and invest less rural Central region are somewhat mixed. The time in household businesses, which are hi- Central and Southern regions exhibit more fe- gher-paying economic activities. In addition, male land ownership and female land manage- women are involved in riskier and lower-pa- ment. However, Because the Northern region is ying activities such as nondiversified farming the richest rural area, it has a larger share of whereas men have higher proportions of far- women working in higher-income activities ming plus formal nonfarming as well as both and earning higher salaries than in the other formal and informal nonfarming activities. In two regions. contrast, men are more involved in wage em- Differences among the regions also emerge ployment. Also, women own fewer parcels of when it comes to poverty status and gender. land compared to men, and of that land only Living in a house with only one female adult im- about half is actually run and controlled by plies a higher probability of being poor than liv- women. Finally, when working in lower-pa- ing in a house with only one male adult, and that ying activities such as agriculture, female gap is wider in the rural Southern region (Ma- land managers are less productive. Howe- lawi’s poorest region). Differences can also be ver, most differences in productivity can be observed with respect to median wages. Men’s attributed to differences in endowments median wages are higher in urban and rural and agricultural inputs: once controlling for Southern regions, equal to women’s median agricultural inputs such as land size, fertili- wages in the rural Central region, and women zer use, farm assets, and time allocation, the earn higher median annual wages than men in sex of the land manager becomes irrelevant. the rural Northern region. These heterogeneities Therefore, access to farm inputs is essential within the country are particularly important to for women to improve their productivity and take into consideration for policy. potentially become less poor. 65 Poverty and Gender in Malawi • Women’s capacity to access services and accu- The lack of capacity to make decisions is re- mulate human capital endowments (critically flected in women’s well-being as well as in important when applying a multidimensional their economic independence. For instance, poverty perspective) is below that of men. The even though female employment is high, wo- overall lower secondary completion rate is men do not perform well once they separate significantly lower for Malawi than the regio- from a partner or become widowed: pover- nal average, and women fare far worse than ty among separated, divorced, or widowed men. In secondary education, a significant women is about 30 percentage points higher proportion of girls drop out of school becau- than among men in the equivalent situations. se of marriage and teenage pregnancy, having This could mean that, although women are potentially significant impacts on future inco- economically active, they are not as economi- mes and poverty. Furthermore, women face cally independent as men. gender-specific health challenges including In light of the multidimensional aspects of high maternal and infant mortality, high ferti- gender equality—and the existing disparities lity and teenage pregnancy rates, and high HIV across endowments, economic opportunities, prevalence. and agency—it will be crucial to initiate com- • Women’s agency—the capacity to make deci- prehensive, multisector efforts to address the sions and act on them—is one of the major dri- gender-specific aspects of poverty. Women’s vers of accumulating endowments and taking access to education and good quality health, advantage of economic opportunities, but it is their ability to generate incomes, and the ca- limited in Malawi, trapping women further into pacity to make decisions for themselves and poverty. This is evidenced by high prevalence their families are in and of themselves import- rates of different forms of violence against ant to promote; and they are drivers of mov- women, including intimate partner violence ing individuals out of poverty. Those efforts and high child marriage rates. In particular, will need to be informed by existing evidence child marriage has negative impacts on po- and to be accompanied by solid monitoring and verty, human capital accumulation, and po- evaluation frameworks to assess progress and tentially labor force participation. When it co- enable course correction along the way. Finally, mes to household decision-making, although the active participation of stakeholders at dif- women’s autonomy has increased in the last ferent levels will be important to ensure buy-in 15 years, it remains low compared to men’s. and feasibility of implementation. Poverty and Gender in Malawi 66 Appendix A Data and Poverty Measurement Details Poverty was estimated at a household level and and only 4 percent of its population report hav- expanded to individuals under the assumption ing a waged job as primary income source, in- that income was uniformly distributed within come was accounted as the value of a household households. Conceptually, poverty rate delim- consumption aggregate. The poverty line was its the population share that is unable to meet drawn by expanding the food poverty line (which basic needs; therefore, its estimation relies on accounts for the cost of obtaining a 2,215 calorie the construction of two major components: an daily intake) to general consumption. Details on income proxy and a poverty line. Motivated by these components’ construction are mentioned the fact that Malawi is an agricultural economy, in the subsequent subsections. CONSUMPTION AGGREGATE The consumption aggregate was made up of time dimensions (Month – District, Month – Ur- food and nonfood components. In the case of ban region, Urban region & National). Quantities food, all major sources of food consumption were allowed to be reported in nonstandard and (purchases, own-production, gifts, and others) local units, which were converted using official were accounted for. Nonstandard local con- NSO-provided conversion factors, which were sumption units were transformed into kilograms collected in a supplementary survey. using the conversion factors provided by the Na- Nonfood components were made up by add- tional Statistical Office (NSO) and household unit ing rent and total expenditure on durable and values constructed by dividing expenditure with nondurable goods. Rental expenditure on dwell- quantity consumed. These were replaced by ings rented from other owners was considered median unit values calculated for each item at a good estimate of the value of housing under the lowest desegregation level possible (at least the assumption of a competitive rental market. 10 observations for item prices by level). Such Therefore, such reported values were consid- disaggregation included both geographical and ered for actual renters. For nonrenters, theoret- 67 Poverty and Gender in Malawi ical self-reported rental values were collected; water, electricity, gas, firewood), and general ex- however, these were considered inaccurate. To penditure (such as charcoal, clothing, footwear, improve their accuracy, information on actual and transport). Sporadic expenditures, such as rental expense is used. A hedonic regression weddings, funerals, and births, were excluded. was estimated using logarithm of rent (for those The analysis relied on reported expenditure val- who are renting) and a hedonic rental value was ues, which were trimmed at the item level. imputed for both renter and nonrenter house- Because temporal price variations can differ holds. These estimates were used to replace significantly across areas, a temporal adjust- outliers in the self-reported rent data. ment was implemented by using a combination For durable goods, use value was estimat- of the unit values of food items from IHS5 and ed on the basis of their age, their reported cur- the official NSO-provided nonfood Consumer rent value, and the number of units owned by Price Index (CPI). These itemized unit values the household. Purchase of durables was as- were combined with their respective average sumed to be uniformly distributed over time. food budget shares in the household survey The estimated lifetime of each durable good to calculate the monthly food price index. The (except for cars and motorcycles) was put at food price index was then combined with the twice the mean age of the item. For cars and nonfood CPI to calculate the overall monthly motorcycles, the distribution was assumed to price index. be skewed, so their lifetime was calculated as A spatial Paasche price index was estimated three times their mean age. Remaining service using food prices from Malawi’s Fifth Integrat- years left for each durable good was calculated ed Household Survey (IHS5, 2019–20) unit val- as its current age minus the estimated lifetime ues and official nonfood CPI for nonfood items. of the good. The ratio of the current value over Weights of the items in the price index came the remaining lifetime of service was used to from IHS5 for food items, whereas those for approximate its annual use. nonfood items came from the regional weight Nondurables expenditure was made by add- of the official NSO nonfood CPI. Finally, food and ing up reported expenditures on education, nonfood price indexes were combined using the health services (including prescription and non- average budget shares of the two consumption prescription drugs), housing utilities (such as aggregates at the regional level. POVERTY LINE Following the cost-of-basic-needs approach, the population in the fifth and sixth deciles of the cost of acquiring enough food for adequate nu- consumption aggregate distribution was chosen trition (2,215 calories per person per day) was as the reference population. For food items to be estimated. To generate a daily food basket, the preselected for the basket, they had to meet fre- Poverty and Gender in Malawi 68 quency and intake-share constraints. Quantities average nonfood consumption of the popula- of each item for the reference basket were es- tion whose food consumption is close to the timated using the sample consumption shares food poverty line. and by rescaling them to meet 2,215 calories Once the poverty line is established, all per person per day. Prices for items were im- households can be categorized as poor or non- puted using national median values after lowest poor depending on whether their per capita ex- aggregate possible. penditure (their welfare indicator adjusted for Ravallion and Bidani’s (1994) approach was household size) is below or above the poverty implemented to generate the IHS5 poverty line line. The poverty headcount, then, can be com- out of the food poverty line. In this approach, puted, indicating the proportion of individuals the nonfood allowance was estimated as the living in poverty. 69 Poverty and Gender in Malawi Appendix B Methodology and Data Most of this paper uses data from the latest household levels were constructed to assess Malawi Integrated Household Survey (the Fifth their evolution over time or to obtain a snapshot Integrated Household Survey [IHS5], 2019–20). of Malawi’s current situation regarding gender This survey is one of the primary instruments gaps in economic opportunities, ability to accu- implemented by the Government of Malawi mulate human capital, and women’s agency. through the National Statistical Office (NSO) to In addition, the poverty rates here exposed monitor and evaluate the changing conditions were estimated for the Malawi Poverty Assess- of Malawian households. The latest round was ment 2021, using the expenditure modules of the implemented in the period between April 2019 household questionnaire of IHS5. As in many Af- and April 2020. The sampling frame is based on rican countries, poverty in Malawi is measured by the listing information and cartography from the contrasting the value of a household consump- 2018 Malawi Population and Housing Census, tion aggregate (as an income proxy) against a including Malawi’s three major regions: Central, poverty line. The use of the consumption/expen- Northern, and Southern. Also, the data are strat- diture aggregate instead of a household income ified at the urban/rural level. The questionnaire aggregate is motivated by the fact that Malawi’s has four separate sections: household question- economy is predominantly agricultural and only 4 naire, agriculture questionnaire, fisheries ques- percent of its population reports having a waged tionnaire, and community questionnaire. Such job as a primary income source. Then, following questionnaires collect very detailed data on a cost-of-basic-needs approach, the cost of ac- multiple topics. Our analysis uses the first two quiring enough food for adequate nutrition line mentioned questionnaires extensively. (which accounts for the cost of obtaining a 2,215 The household modules were used to an- calorie daily intake) was estimated, obtaining the alyze both individual- and household-level extreme poverty line. Afterward, the poverty line variables such as main economic activities, edu- was drawn by expanding the food poverty to gen- cation, time allocation, migration, poverty, trans- eral consumption (see appendix A for more de- fers, and so on. Indicators at the individual and tails on poverty measurement). Poverty and Gender in Malawi 70 In contrast to the use of the household ques- ership of farm assets were computed. Mean com- tionnaire, the agricultural modules were used parison tests by gender of land manager were to assess agriculture-related questions such conducted, exhibiting significant differences in as productivity, agricultural inputs, agricultural agricultural inputs for production. Consequent- products, harvest use, and so on. For better un- ly, to identify whether differences in productivity derstanding gendered differences in agricultural were due to such differences in agricultural in- outcomes and particularly agricultural produc- puts or due to other sources of unproductivity, tivity, a productivity measure had to be built. For regression analyses were conducted. To do so, this finality, productivity was defined as the har- harvested value and poverty were chosen as vested value over the total planted area. We did dependent variables and all agricultural inputs not use total land size, because not all plots were that could be collected from IHS5 together with completely planted with crops. Harvested value a dummy on land manager’s gender were used is the market value of all the crops grown by the as independent variables. In addition, average household (regardless of their final use). Non- rainfall; household head education; whether the standard local output units were transformed farm produces food crops, cash crops, or both; into kilograms using the NSO-provided conver- whether it sells them or not; and district con- sion factors. Market values were imported out of trols were included in the regression. If when food consumption aggregate whenever possible controlling for agricultural production inputs, and replaced with sale unit values when miss- the dummy variable on land manager’s gender ing. Sale values were constructed by dividing to- was significant, it would mean that differences tal sale value of a crop by its sale quantity. These in productivity or poverty are beyond the inputs were replaced by median unit values calculated used for production. By contrast, if the dummy for each crop at the lowest disaggregation lev- variable was not significant, it would mean that el possible (at least 10 observations for item differences in inputs and other controls explain prices by level). Such disaggregation included differences in outcomes (poverty and harvested both geographical and time dimensions (Month value) beyond the gender of the land manager. – District, Month – Urban region, Urban region Finally, some other sources such as the & National). Then, the ratio of harvested value School to Work Transition Survey, Demographic over planted area was computed to obtain the and Health Surveys, United Nations Joint Pro- productivity measure. gramme on HIV/AIDS, and the World Bank’s Afterward, different indicators on quantity of World Development Indicators were also con- used fertilizers, quantity of used seeds, received sulted for particular topics that are not covered coupons, allocated time to the activity, and own- in the IHS5. 71 Poverty and Gender in Malawi Appendix C Women, Business and the Law 2021 Topic Question Answer Mobility Can a woman choose where to live in the same way as a man? No Can a woman travel outside her home in the same way as a man? Yes Can a woman apply for a passport in the same way as a man? No Can a woman travel outside the country in the same way as a man? Yes Workplace Can a woman get a job in the same way as a man? Yes Does the law prohibit discrimination in employment based on gender? Yes Is there legislation on sexual harassment in employment? Yes Are there criminal penalties or civil remedies for sexual harassment in Yes employment? Criminal penalties Yes Civil remedies No Pay Does the law mandate equal remuneration for work of equal value? Yes Can a woman work at night in the same way as a man? Yes Can a woman work in a job deemed dangerous in the same way as a man? Yes Jobs deemed hazardous Yes Jobs deemed arduous Yes Jobs deemed morally inappropriate Yes Can a woman work in an industrial job in the same way as a man? Yes Mining Yes Construction Yes Factories Yes Agriculture Yes Poverty and Gender in Malawi 72 Topic Question Answer Energy Yes Water Yes Transportation Yes Other Yes Is there no legal provision that requires a married woman to obey her Yes Marriage husband? Can a woman be “head of household” or “head of family” in the same way as Yes a man? Is there legislation specifically addressing domestic violence? Yes Can a woman obtain a judgment of divorce in the same way as a man? Yes Does a woman have the same rights to remarry as a man? Yes Parenthood Is paid leave of at least 14 weeks available to mothers? No Length of paid maternity leave 56 days Does the government administer 100% of maternity leave benefits? No Is there paid leave available to fathers? No Length of paid paternity leave 0 Is there paid parental leave? No Shared days 0 Days for the mother 0 Days for the father 0 Is dismissal of pregnant workers prohibited? Yes Entrepreneurship Does the law prohibit discrimination in access to credit based on gender? No Can a woman sign a contract in the same way as a man? Yes Can a woman register a business in the same way as a man? Yes Can a woman open a bank account in the same way as a man? Yes Assets Do men and women have equal ownership rights to immovable property? Yes Do sons and daughters have equal rights to inherit assets from their parents? Yes Do female and male surviving spouses have equal rights to inherit assets? Yes Does the law grant spouses equal administrative authority over assets during Yes marriage? Does the law provide for the valuation of nonmonetary contributions? Yes 73 Poverty and Gender in Malawi Topic Question Answer Is the age at which men and women can retire with full pension benefits the Yes Pension same? Age (women) 50 Age (men) 50 Is the age at which men and women can retire with partial pension benefits Yes the same? Age (women) - Age (men) - Is the mandatory retirement age for men and women the same? Yes Age (women) - Age (men) - Are periods of absence from work due to childcare accounted for in pension No benefits? Source: Women, Business and the Law database (https://wbl.worldbank.org/en/wbl). Poverty and Gender in Malawi 74 References Asfaw, S., and G. Maggio. 2018. Gender, Weather Beegle, K., A. Coudouel, and E. M. Monsalve. Shocks and Welfare: Evidence from Mala- 2018. Realizing the Full Potential of Social wi. Journal of Development Studies, 54 (2). Safety Nets in Africa. Washington, D.C. : pp. 271-291. World Bank Group. Azevedo, J. P., M. Favara, S. E. Haddock, L. F. Beegle, Kathleen, Luc Christiaensen, Andrew Lopez-Calva, M. Müller, and E. Perova. Dabalen, and Isis Gaddis. 2016. Poverty in a 2013. “Teenage pregnancy and opportu- Rising Africa. Washington, DC: World Bank. nities in Latin America and the Caribbean: Beegle, K., and M. Poulin. 2013. “Migration and On Teenage Fertility Decisions, Poverty the Transition to Adulthood in Contempo- and Economic Achievement.” World Bank, rary Malawi.” Annals of the American Acad- Washington, DC. emy of Political and Social Science 648 (1). Baird, S. J., R. S. Garfein, C. T. McIntosh, and Bisika, T. 2008. “Do Social and Cultural Factors B. Ozler. 2012. “Effect of a Cash Transfer Perpetuate Gender Based Violence in Ma- Programme for Schooling on Prevalence of lawi?” Gender & Behaviour 6 (2): 1884–96. HIV and Herpes Simplex Type 2 in Malawi: Boone, R., K. Covarrubias, B. Davis, and P. Win- A Cluster Randomised Trial.” Lancet 379 ters. 2013. “Cash Transfer Programs and (9823): 1320–29. Agricultural Production: The Case of Mala- Bazile J., J. Rigodon, L. Berman, V. M. Boulanger, wi.” Agricultural Economics 44 (3): E. Maistrellis, P. Kausiwa, and A. Yamin. 365–78. 2015. “Intergenerational Impacts of Ma- CEDAW (United Nations Committee on Elimi- ternal Mortality: Qualitative Findings from nation of Discrimination against Women). Rural Malawi.” Reproductive Health 12 2013. “Concluding Observations on the (Suppl 1): S1. Sixth Periodic Report of Malawi.” United Becker, Gary S. 1995. “Human Capital and Pov- Nations, Geneva. erty Alleviation.” HRO Working Paper 52, CEDAW (United Nations Committee on Elimi- Human Resources Development and Oper- nation of Discrimination against Women). ation Policy, World Bank, Washington, DC. 2015, “Concluding Observations on the 75 Poverty and Gender in Malawi Seventh Periodic Report of Malawi.” United Poverty Economists. World Bank. Washing- Nations, Geneva. ton DC. Chasweka, Robert, Angela Chimwaza, Alfred “Djuikom, Marie Albertine; van de Walle, Dom- Maluwa, and Jon Oyvind Odland. 2012. inique. 2018. Marital Shocks and Women’s “The Magnitude of Domestic Violence Welfare in Africa. Policy Research Working against Pregnant Women in Malawi.” Jour- Paper;No. 8306. World Bank, Washington, nal of Research in Nursing and Midwifery 1 DC. © World Bank. (2): 17–21. Dorward, A., and E. Chirwa. 2011. “The Malawi Chatora, Arthur. 2015. “Female Genital Mu- Agricultural Input Subsidy Programme: tilation Silently Practiced in Malawi 2005/06 to 2008/09.” International Journal – Traditional Chiefs.” This Is Africa, No- of Agricultural Sustainability 9 (1): 232–47. vember 26, 2015. https://thisisafrica. Gender Empowerment Network GENET. 2013. me/politics-and-society/female-genital- Information on Genet Malawi’s Fight against nal-chiefs-say/ Child Marriage. Access online at: https:// Chigawa, M. 1987. “Customary Law Marriages www.ohchr.org/Documents/Issues/Wom- and Social Development: De Jure Marriag- en/WRGS/ForcedMarriage/NGO/GENET- es at Customary law in Malawi.” Malawi.docx Colbourn, Tim, Sonia Lewycka, Bejoy Nambi- Girls Not Brides. 2017. “Malawi: Constitution No ar, Iqbal Anwar, Ann Phoya, and Chisale Longer Allows Child Marriage.” Girls Not Mhango. 2013. “Maternal Mortality in Brides, February 15, 2017 (updated April Malawi, 1977–2012.” BMJ Open 2013; 26, 2017). https://www.girlsnotbrides.org/ 3:e004150. articles/malawi-constitution-no-longer-al- Creti, P., and S. Jaspars, eds. 2006. Cash-Trans- lows-child-marriage/. fer Programming in Emergencies. Oxford: Goldstein, M. and C. Udry. 2008. The Profits Oxfam Great Britain. of Power: Land Rights and Agricultural Dake, F., L. Natali, G. Angeles, J. de Hoop, S. Investment in Ghana. Journal of Political Handa, and A. Peterman. 2018. “Cash Economy, 2008, vol. 116, issue 6, 981-1022 Transfers, Early Marriage, and Fertility Hill, R. V. and M. Vigneri. 2011. Mainstreaming in Malawi and Zambia.” Studies in Family gender sensitivity in cash crop market Planning 49 (4): 295–317. supply chains. No 289013, ESA Working Danida (Danish International Development Papers from Food and Agriculture Organi- Agency. 2011. “Agricultural Input Subsidies zation of the United Nations, Agricultural in Sub-Saharan Africa.” Ministry of Foreign Development Economics Division (ESA) Affairs of Denmark. Hoffman SD. Updated estimates of the conse- de Paz and Muller. 2021. Poverty Assessments quences of teen childbearing for mothers. and Gender Equality—A Guidance Note for In: Hoffman SD, Maynard RA, editors. Kids Poverty and Gender in Malawi 76 having kids: Economic costs & social conse- icy Research Working Paper 9151. World quences of teen pregnancy. Washington, DC: Bank. Washington DC. Urban Institute Press; 2008. pp. 74–92. Kilic, T., A. Palacios-López, and M. Goldstein. Human Rights Watch. 2014. “‘I’ve Never Experi- 2015. “Caught in a Productivity Trap: A enced Happiness: Child Marriage in Mala- Distributional Perspective on Gender Dif- wi.” Human Rights Watch, March 6, 2014. ferences in Malawian Agriculture.” World https://www.hrw.org/report/2014/03/06/ Development 70 (C): 416–63. ive-never-experienced-happiness/ Klugman, J., L. Hanmer, S. Twigg, T. Hasan, J. child-marriage-malawi. McCleary-Sills, J. Santamaria. 2014. Voice Kabeer, N. 2005. Gender equality and wom- and Agency: Empowering Women and Girls en’s empowerment: A critical analysis of for Shared Prosperity. Washington, DC: the third millennium development goal 1, World Bank Group. World Bank. Gender & Development, 13:1, 13-24, DOI: Kruger, D. I., M. Berthelon, and R. R. Soares. 10.1080/13552070512331332273 2010. “Allocation of Children’s Time along Kamlongera, A. P. 2008. “Malawian Women’s Gender Lines: Work, School, and Domestic Participation in State Politics: What Are the Work in Brazil.” In Child Labor and the Tran- Constraints?” Gender and Development 16 sition between School and Work, edited by (3): 471–80. R. K. Q. Akee, E. V. Edmonds, and K. Tatsir- Kamyongolo, Ngeyi Ruth, and Bernadette amos, 161–92. Bingley, UK: Emerald Group Malunga. 2011. “The Treatment of Con- Publishing Ltd. sent in Sexual Assault Law in Malawi.” The Kruger, D.I and M. Berthelon (2012), “Education Equality Effect, May 2011. http://theequali- consequences of adolescent motherhood tyeffect.org/pdfs/ConsentPaperMalawi.pdf. in Chile,” Background Paper for: Azevedo Karamba, R. Wendy, and Paul C. Winters. 2015. et al 2013. “Gender and Agricultural Productivity: Im- Lema, Valentina, Josephine Changole, and Car- plications of the Farm Input Subsidy Pro- olyn Kanyighe. 2005. “Maternal Mortality gram in Malawi.” Agricultural Economics 46 at the Queen Elizabeth Central Teaching (3): 357–74. Hospital, Blantyre, Malawi.” East African Kevane, M. 2004. Women and Development in Medical Journal 82 (1): 3–9. Africa: How Gender Works. Boulder, CO: Levine, R., Lloyd, C., Greene, M., & Grown, C. Lynne Rienner. 2004. Published online by (2008). Girls count. A global investment and Cambridge University Pre action agenda. Washington, DC: Center for Kilic, T., H. Moylan, and G. Koolwal. 2020. Getting Global Development the (Gender-Disaggregated) Lay of the Land: Lomba, Philo. 2014. “Widow Cleansing in Mala- Impact of Survey Respondent Selection on wi.” American International Journal of Con- Measuring Land Ownership and Rights. Pol- temporary Research 4 (1). 77 Poverty and Gender in Malawi Malawi Human Rights Commission. 2005. “Cul- http://www.unaids.org/sites/default/ tural Practices and Their Impact on the files/country/documents/MWI_narrative_ Enjoyment of Human Rights, Particularly report_2015.pdf the Rights of Women and Children in Ma- Ng’ong’ola, C. 1982. “The Design and Imple- lawi.” Malawi Human Rights Commission, mentation of Customary Land Reforms in Lilongwe. Central Malawi.” Journal of African Law 26 Mgawadere, Florence, Regine Unkels, Abigail (2): 115–32. Kazembe, and Nynke van den Broek. 2017. Nove, Andrea, Zoë Matthews, Sarah Neal, and “Factors Associated with Maternal Mortal- Alma Virginia Camacho. 2014. “Maternal ity in Malawi: application of the Three De- Mortality In Adolescents Compared with lays Model.” BMC Pregnancy and Childbirth Women of Other Ages: Evidence from 17, article 219. 144 Countries.” Lancet Global Health 2 (3): Ministry of Health, Malawi. 2016. “Malawi Pop- e155–64. ulation-Based HIV Impact Assessment: NSO (National Statistical Office). 2010. “Gender MPHIA 2015–2016. Summary Sheet. and Development Index 2010.” Government https://www.hiv.health.gov.mw/images/ of Malawi. Documents/MALAWIFactsheet.pdf. NSO (National Statistical Office). 2012. “Gender Muller, M., S. Melibaeva, A. L. Machado, and and Development Index 2011.” Government U. Casabonne. 2019. “Making Inroads for of Malawi. http://www.nsomalawi.mw/ Women: A Qualitative Study on Constraints images/stories/data_on_line/economics/ and Opportunities of Women’s Equal Par- Gender/MALAWI_GENDER_AND_DEVELOP- ticipation in the Roads Sector in Malawi.” MENT_INDEX%20-June%202012.pdf. World Bank, Washington, DC. NSO (National Statistical Office, Malawi). 2017. Muñoz et al. 2018. Gender Differences in Pover- “Malawi Demographic and Health Survey ty and Household Composition through the 2015–16.” NSO, Zomba, Malawi. Lifecycle A Global Perspective. Policy Re- Pachai, Bridglal. 1978. Land and Politics in Ma- search Working Paper 8360. World Bank. lawi, 1875–1975. Kingston, Ontario: Lime- Mutenje, Munyaradzi, Henry Kankwamba, Julius stone Press. Mangisonib, and Menale Kassie. 2016. “Ag- Psacharopoulos, G., and H. A. Patrinos. 2018. ricultural Innovations and Food Security in “Returns to Investment in Education: A Malawi: Gender Dynamics, Institutions and Decennial Review of the Global Literature.” Market Implications.” Technological Fore- Education Economics 26 (5): 445–58. casting & Social Change 103 (February): Peters, Pauline E. 2010. “‘Our Daughters Inherit 240–48. Our Land, but Our Sons Use Their Wives’ NAC (Malawi National AIDS Commission). fields’: Matrilineal/matrilocal Land Tenure 2015. “Malawi AIDS Response Progress and the New Land Policy in Malawi.” Jour- Report 2015.” Government of Malawi. nal of Eastern African Studies 4 (1): 179–99. Poverty and Gender in Malawi 78 Price, A., J. Glynn, M. Chihana, N. Kayuni, S. for 2017.” Bureau of Democracy, Human Floyd, E. Slaymaker, G. Reniers, B. Zaba, E. Rights and Labor. McLean, F. Kalobekamo, O. Koole, M. Ny- Vaughan, R. P. 2010. Girls’ and women’s edu- irenda, and A. Crampin. 2016. “ Sustained cation within Unesco and the World Bank, 10-Year Gain in Adult Life Expectancy 1945–2000. Journal of Comparative and Following Antiretroviral Therapy Roll-Out International Education, 40(4), 405–423, in Rural Malawi: July 2005 to June 2014.” White, Seodi. 2007. Malawi: Country Gender International Journal of Epidemiology 46 Profile. Japan International Cooperation (2): 479–91. Agency, Tokyo. https://www.jica.go.jp/en- Quisumbing, A. 1996. Male-female differences glish/our_work/thematic_issues/gender/ in agricultural productivity: Methodological background/pdf/e07mal.pdf. issues and empirical evidence. World Devel- Whiteside, Martin. 2000. “Ganyu Labour in Ma- opment, 1996, vol. 24, issue 10, 1579-1595 lawi and Its Implications for Livelihood Se- QuotaProject. 2013. Global Database of Quota curity Interventions—An Analysis of Recent for Women: Malawi. http://www.quotaproj- Literature and Implications for Poverty ect.org/uid/countryview.cfm?ul=en&coun- Alleviation.” AgREN Network Paper 99, UK try=132#additional. Department for International Development. Ravallion, M. and B. Bidani. 1994. How Robust Is WHO (World Health Organization). 2015. WHO a Poverty Profile? The World Bank Econom- Country Cooperation Strategy 2008-2013: ic Review, Volume 8, Issue 1, January 1994, Malawi. Geneva: WHO. Pages 75–102, https://doi.org/10.1093/ WLSA Malawi (Women and Law in Southern wber/8.1.75 Africa–Malawi). 2002. Dispossessing The UNAIDS (United Nations Joint Programme on Widow: Gender Based Violence in Malawi. HIV/AIDS). 2019. “UNAIDS Data 2019.” Blantyre, Malawi: Christina Literature As- United Nations, Geneva. sociation in Malawi. UN DESA (United Nations Department of Eco- Wodon, Quentin T., Chata Male, Kolobadia Ada nomic and Social Affairs). 2017. “World Nayihouba, Adenike Opeoluwa Onagoruwa, Population Prospects: The 2017 Revision.” Aboudrahyme Savadogo, Ali Yedan, Jeff United Nations, New York. Edmeades, Aslihan Kes, Neetu John, Lyd- UNFPA (United Nations Population Fund). 2013. ia Murithi, Mara Steinhaus, and Suzanne “Motherhood in Childhood: Facing the Chal- Petroni. 2017. “Economic Impacts of Child lenge of Adolescent Pregnancy.” State of Marriage: Global Synthesis Report.” World the World Population 2013, United Nations, Bank, Washington, DC. New York. World Bank. 2012. World Development Report US Department of State. 2017. “Malawi: Coun- 2012: Gender Equality and Development. try Reports on Human Rights Practices Washington, DC: World Bank. 79 Poverty and Gender in Malawi World Bank. 2018a. Poverty and Shared Prosper- ress and the Challenges Ahead. ity 2018: Piecing Together the Poverty Puz- World Bank. zle. Washington, DC: World Bank. World Bank. 2018c. “Malawi Economic Monitor: World Bank. 2018b. Kenya Gender and Poverty Investing in Girl’s Education.” World Bank, Assessment 2015/16—A Decade of Prog- Lilongwe, Malawi. Poverty and Gender in Malawi 80