Addressing Food Security in Africa Via Multiple Livelihood Strategies of Women Farmers Christina H

Food Policy 26 (2001) 177–207 www.elsevier.com/locate/foodpol

Addressing food security in Africa via multiple livelihood strategies of women farmers Christina H. Gladwin a,*, Anne M. Thomson b, Jennifer S. Peterson c, Andrea S. Anderson d a Food and Resource Economics Department, Box 110240 IFAS, University of Florida, Gainesville, FL 32611, USA b 66 Causewayhead Road, Stirling FK9 5EZ, UK c Africare, Niamey, Niger d Santa Fe Community College, Gainesville, FL, USA

Received 17 November 1997; received in revised form 14 September 2000; accepted 5 December 2000

Abstract

Because food insecurity is primarily a problem of low household incomes and poverty, and not just inadequate food production, projects and programs for food insecure African farmers which aim at increasing production of subsistence crops may be ineffective. Instead, government should look for ways to improve returns to farmers’ resources in a broader context, which may include expanded opportunities for non-farm microenterprises and agricultural labor. This has been the conventional wisdom since the writings of Amartya Sen. Still unclear, however, are the implications of his thinking for the roles of African women farmers who are traditionally the food-crop producers in Africa and are often food insecure. Immediate expansion of income-earning activities such as cash cropping and non-farm microenterprises may not be possible for women in male headed households in many African societies where cash income is seen as part of the male domain. In addition, women farmers may need a long adjustment period to diversify their income sources fully because most African countries are at the early stages of structural transformation. Different developmental interventions, both in policy and in technology, are therefore needed to address food security and economic transformations in Africa in the short and long term.  2001 Published by Elsevier Science Ltd.

Keywords: Food security; Livelihood strategies; Women; Income diversiﬁcation

* Corresponding author. Tel.: +1-352-392-1881 ext. 326; fax: +1-352-392-9898. E-mail address: [email protected]ﬂ.edu (C.H. Gladwin).

0306-9192/01/$ - see front matter  2001 Published by Elsevier Science Ltd. PII: S 03 06 -9192(00)00045-2 178 C.H. Gladwin et al. / Food Policy 26 (2001) 177–207

Introduction

All too frequently the problem of improving food security in Africa has been addressed, both by governments and agricultural research institutes by programs aimed at increasing the production of subsistence crops by food-insecure African farmers1. However, food insecurity is primarily a problem of low household incomes and poverty, and not just inadequate food production. Instead, government should look for ways to improve returns to farmers’ resources in a broader context, which may include expanded opportunities for non-farm microenterprises, cash cropping, and agricultural labor. This has been the conventional wisdom since the writings of Amartya Sen (1981). Sen’s message, however, has still not been heard in sub-Saharan Africa where it is frequently assumed that the focus has to be on increasing aggregate food production. This goal, long the cornerstone of successful Green Revolutions in Asia and Latin America, has now inspired present-day attempts at technology transfer by programs such as Sasakawa Global 2000 (SG 2000) which operates in eight African countries (Borlaug and Dowswell, 1995). To encourage participation, Nobel prize winner Borlaug, President Jimmy Carter, and Rohei Sasakawa need only point to indicators such as per capita food production growth rates to show that Africa has lost the ability to feed itself. Occasionally, they highlight the differences between China’s recent successes and Africa’s recent failures: in 1992–94, China’s average cereal yields were 4482 kilograms per hectare (kg/ha) and the highest of the developing world; Africa’s were the lowest at 1023 kg/ha. In contrast, sub-Saharan Africa’s population growth rates in 1990–1995 were the highest in the world at 3% per annum, while China’s were a low 1.4% per annum. These indicators clearly show that Africa’s per capita food production has not kept up with its population growth rates. It is a continent of farmers which imports one-third of its food grains; nine of its ten largest countries are net importers of food. Yet most African countries are agriculturally-based, with 75–85% of the labor force still employed in agriculture and most of the GDP still generated by the agricultural sector. Tomich et al. (1995) term them CARLs, countries with abundant rural labor. Characteristically, they are at the earliest stages of structural transformation, which means they are years — even decades — away from a turning point when their economies will diversify from one mostly dependent on agriculture to one with

1 The common agro-technical assumption that more food crop production should give more food security does not always hold. The policy issues are rather more complicated, because increasing aggregate food production impacts on food-insecure households only indirectly and doesn’t answer the question: Whose food production are we talking about? Estimates of a national “food gap” have very limited relevance because food supplies are usually badly distributed in an economy. Food is wasted by the rich and often bypasses the hungry people, so that estimates of an aggregate food gap don’t tell us much about how many and which people are hungry. National production figures are often used by policy planners to calculate a “national food gap” in order to get food aid from donor countries. Unfortunately, the food aid then depresses local production by depressing its price or, if it enters the commercial sector, never gets to the poor who need it. C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 179 developed agricultural, manufacturing, and service sectors, and in the process increase agricultural productivity (Tomich et al., 1995: 14). What are some of the causes of Africa’s low agricultural productivity? Among the factors mentioned besides high population growth rates are 25 years of mostly poor weather; too few roads, vehicles, and telephones; predatory governments and officials; public policies which lurch from extreme to extreme; and devastating regional and ethnic conflicts. In addition, there is a factor called “the invisible factor” by the women-in-development (WID) literature specializing in Africa. Women are the food producers in sub-Saharan Africa (Boserup, 1970) in contrast to the smallholders of Latin America and Asia, most of who were men during their “Green Revol- utions”. The constraints facing women farmers are proving to be greater stumbling blocks than those faced by male smallholders in Latin America and Asia during the 1960s and 1970s. These include women’s lack of access to: land (women beg for land rather than own it), capital or credit or cash (women don’t usually raise cash crops which are in the male domain), fertilizer or manure, technological training and extension services, the political arena, and the non-farm labor markets (women lack education) (Gladwin, 1991; Gladwin and McMillan, 1989). Gender is called “an invisible factor” because gender-related constraints that lower women’s productivity are almost never mentioned as explanations of Africa’s food security problems (Eicher 1982, 1995; Smale, 1995), in spite of their being a major reason why the findings of Sen have not been taken on board by African policy makers. They are mentioned in the women in development (WID) literature, but are delinked from the food security literature. This is in spite of Boserup’s (1970) treatise that clearly situated her discussion of women’s roles and Africa’s “female farming systems” within an overall framework of economic development, as well as more recent evidence from nutritional studies that women’s schooling, women’s status relative to men’s, per capita food intake, and per capita incomes are important deter- minants of child nutrition in Africa (Pinstrup-Andersen et al., 1999; SCN/IFPRI, 1999). In the pre-Sen era, when development thinking could be summarized as “more food crop production should give more food security”, WID Africanists proposed straightforward solutions to food insecurity. Just as smallholder food producers in Asia and Latin America were targeted in the 1960s and 1970s with yield-increasing inputs of production (hybrid seeds, credit, fertilizer, manure) in order that Green Revolution yields might be produced, so African food producers — who just happen to be women — should be targeted in the 1980s and 1990s with the same. A few programs were developed to target credit, fertilizer, hybrid seeds, agroforestry seedlings directly at women, usually through women’s clubs (e.g. the VEZA/HODESA program; D’Arcy, 1998). They were either failures in implementation because the men in male headed households (MHHs) decided if and to what extent the women would repay the credit, or they died when unsustainable credit programs failed (Adams and Von Pischke, 1995), or they were given the axe along with other good projects during the era of structural adjustment programs. The current thinking about food security, that it is an issue of household income and poverty and not just inadequate aggregate food production, challenges programs 180 C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 which encourage women to just grow more food crops to improve their food security. In this paper, we propose a more complex strategy and suggest that different developmental interventions, both in policy and in technology, are needed to address the food insecurity of women farmers. What is needed, as a general rule, are interventions to increase women’s incomes and help make their livelihoods more sustainable. Yet African women farmers may need a long adjustment time period to diversify their income sources fully because most African countries are at the early stages of structural transformation. Moreover, the particular form these interventions take should vary, depending on the assets and household composition of the women being targeted. In many societies where cash is considered to be in the male domain, women in female headed households (FHHs) and women in MHHs cannot be treated as a homogeneous group. Immediate expansion of married women’s income-earning activities such as cash cropping and non-farm microenterprises may not be possible. In addition, younger women with high demands on their labor cannot be treated like older women with more adult labor (and cash income) available. This paper follows Boserup in attempting to link food security issues in Africa with household-level livelihood systems whose characteristics are in large part determined by gender roles which can change over time. Like Boserup, we attempt to situate the African woman’s role in food security within a theoretical framework that assumes economic development is a long-term process of structural transformation whereby a mostly agrarian society is steadily transformed and diversified into a moderately industrialized and urbanized one in which women are involved (Tomich et al., 1995). To do that, in Section 2 we present a profile of a very food-insecure woman and ask, why is she food insecure? In Section 3, we present linear programming (LP) results outlining the conditions under which she can become food secure, as well as present evidence of women’s multiple livelihoods strategies; and in Section 4, we discuss the characteristics of many African countries which limit the immediate expansion of women’s cash income. In the concluding section, we present a four- pronged strategy to help women achieve more sustainable livelihoods.

Proﬁle of a food-insecure woman farmer

In this paper, we propose to broaden the context of the debate on food security for women farmers in sub-Saharan Africa and do away with the assumption that food security necessarily means their growing more subsistence crops. Food security is better defined as sufficient food consumption by all people at all times for a healthy and productive life (Thomson and Metz, 1997). Chronic food insecurity is a long- term problem caused by lack, at the household level, of income or assets to produce or buy food adequate for the household. Transitory food insecurity is a short-term food security problem caused by a shock to the food production or economic system, where income or resources necessary to adjust to the shock are not available. It would thus seem more appropriate to start off a discussion about the African woman’s role in food security by asking the question, why are African households, especially those headed by women, food insecure? The specific situation of the C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 181

African household varies from country to country and within countries, so it is difficult to raise the question on a very general level. We do know that many African countries are CARLs, countries with abundant rural labor (Tomich et al., 1995), where because 85% of the population lives in the rural sector and depends on agriculture either directly through production, or indirectly through providing labor to farmers for their income, the link between access to food and agricultural production is very strong. This is because agricultural production is the basis of most households’ source of income. Yet agricultural production may not be the rural household’s only source, or even their most important, source of income. To be food secure, rural women must have multiple livelihood strategies, and they recognize this fact. In Africa as in other parts of the world, they are farmers, petty traders, food processors, and engage in informal labor markets (Pearce et al., 1996). The reason for this is that none of the strategies on their own are capable of sustaining them. To illustrate this point, we start with an examination of their resources and income sources at the household level, and profile the case of a land-scarce FHH in Zomba, Malawi, whose main off-farm income opportunity is (ganyu) labor. Why are we focusing on FHHs, when they account for less than half of adult women farmers, and why those in land-scarce situations? Simply because FHHs tend to be in the more impoverished category, and land-scarce situations are the most common and pressing scenario in Africa today2. When women farmers are primarily land scarce, policy makers should look at what is possible on the land available. The case of Malawi shows this clearly. Malawi is the sixth poorest country in the world with 41% of the rural population (16.4% FHHs and 24.6% MHHs) operating Ͻ0.5 ha of land and producing enough food to last only 3–4 months of the year. In fact most of the rural population, 70% by some estimates (Peters 1992, 1993), are not self-sufficient in food but are net purchasers. This is because income distribution is very unequal in Malawi (Lele, 1990), largely as a result of bad policy in the past thirty years. This, combined with the low level of average income or GDP per capita, means that many households in Malawi are food insecure. This is especially true for FHHs in Malawi, who constitute 30% of all rural smallholder households but represent 42% of the rural poverty gap, using the 40th percen- tile income cutoff as a measure of poverty (World Bank, 1996: 30). They also comprise 40% of the 41% of smallholders with Ͻ1/2 ha of land (World Bank 1996: 75). Table 1 summarizes the family’s food consumption requirements, cropping pattern, and food security prospects for a FHH with less than one-third of a hectare of land. It is a household comprised of 3.5 consumption units requiring the consumption of 700 kg of maize a year. This household cultivates 0.29 ha of land, with 0.25 ha

2 In more land-abundant situations in Africa, interventions to assist rural women might differ because the major factor limiting women’s production would then be a shortage of labor, as women are responsible for reproductive tasks within the household as well as food production (Due, 1991; Due and Gladwin, 1991; Guyer with Idowu, 1991; Jones, 1983; Moock, 1976). In these cases, policy makers should examine closely the labor implications of recommended technology packages, including those aimed at replenishing Africa’s depleted soils (Sanchez et al., 1997). We return to this theme in the conclusion. 182 C.H. Gladwin et al. / Food Policy 26 (2001) 177–207

Table 1 Proﬁle of consumption and production of a FHH in Malawi, whose family food requirement=700 kg maize/year or 58.3 kg per month, before and after August 1998 devaluation of the Malawi Kwacha (K 27/US$ to K 44/US$)

Old technology, status Pre-devaluation: new Post-devaluation: new quo technology with hybrid technology and increase in maize seed, fertilizer maize and fertilizer prices

Land in cultivation 0.29 ha 0.29 ha 0.29 ha Cropping pattern 0.25 ha local maize 0.25 ha hybrid maize 0.25 ha hybrid maize 0.04 ha groundnuts 0.04 ha groundnuts 0.04 ha groundnuts Maize inputs/ha 0 156 kg CAN and 25 175 kg CAN and 25 kg kg hybrid maize seed hybrid maize seed Maize inputs on 1/4 ha 0 39 kg CAN and 6 kg 44 kg CAN and 6 kg of of hybrid maize seed hybrid maize seed Input costs 0 MK 645a MK 1090d Inputs costs in maize 0 165 kg maizeb 168 kg maizee equivalents Yields maize/ha 868 kg/ha 2267 kg/hac 2375.9 kg/hac Total maize yields 217 kg 567 kg 594 kg Net yields of maize 217 kg 401.5 kg 426 kg (minus costs) Months of maize 3.7 6.9 7.3 consumption Food security Chronic Chronic Chronic

a Pre-devaluation scenario: at pre-devaluation prices [a 50-kg bag of CAN (20.5–0–0) costs Malawi Kwacha MK 445/bag in 1997/98, maize is valued at MK 3.9 per kg], the farmer optimally applies 156 kg/ha or 39 kg on 1/4 ha and also 6 kg hybrid maize seed for MK 200 in October 1997, for a total of MK 645. b Maize is valued at MK 3.9 per kg (or MK 195 per 50-kg bag). c This assumes the national response function of maize to nitrogen of Benson (1997: Table 4, p. 8): Y=1417+30.8NϪ0.132N2. These yield estimates are much higher than those reported by farmers in personal interviews; but even with these high estimates, this farmer is caught in the trap of chronic food insecurity. d Post-devaluation scenario: at these prices, the optimal quantity of nitrogen is now 37 kg of CAN (20.5–0–0), so the farmer buys a 50-kg bag of CAN costing MK 700 per bag in 1999, and also pays MK 390 for hybrid maize seed, for total costs of MK 1090. e Maize is now valued at MK 6.5 per kg. under local maize and 0.04 ha under groundnuts. Using no fertilizer or hybrid seed, this FHH produces only 217 kg of maize (31% of its consumption requirements), and 15 kg of groundnuts. After just three and a half months, or longer if they stretch consumption, the family will run out of food. The rest of the year’s food supplies have to be made up from off-farm income opportunities, most probably ganyu, informal piece-work labor paid in maize. If the FHH switches from local maize to hybrid maize, however, and applies the optimal amount of 32 kg/ha of nitrogen fertilizer from calcium ammonium nitrate (CAN)3 her yields of maize would more than double

3 Women farmers have many good reasons not to switch from local to hybrid maize, including processing losses with dent (soft) hybrids (Byerlee and Heisey 1996: 262–264). We use fertilized hybrid C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 183 from 217 kg to 567 kg on her 0.25 ha4. Her costs would also increase from 0 to MK 645; but after subtracting costs of fertilizer and seed, she easily doubles her maize production. This is true at both pre-devaluation and post-devaluation prices. What is the problem? After subtracting her costs, there is enough maize to feed the family for only 7 months — little more than half a year — with the new technology. Increasing yields of food crops of a typical female-headed household — even more than doubling yields — is not enough to cover the yearly food consumption requirements of the family. There is just too little land at the household’s disposal. Other ways are also needed to guarantee its food security. The policy solution for the woman heading up this female-headed household is therefore to diversify her land use, and take some small amount of land out of the subsistence crop and plant it to a cash crop. What happens to the disposable cash income of this almost-landless FHH if she does plant a cash crop? Anderson’s use of a LP simulation of a female-headed household in Malusa, Zomba, Malawi, as part of the University of Florida’s “Gender and Soil Fertility in Africa” Soils CRSP (collaborative research support program) shows the effect of this and other interventions on total household income of Ella, a FHH who heads a chronically food- insecure household.

Modeling multiple livelihood systems of women farmers

Modeling the multiple livelihood systems of individual farm households is possible with LP models. LP models allow us to see why households choose the livelihood strategies that they do, given their resources and constraints. They also predict the effects of possible changes to the system by asking “What if?” questions of the LP model (Hildebrand, 2001). LP models simulate the complex farming and livelihood system of smallholder households by including the many different crops, intercrops, and income-earning activities as different columns in the program. Included in the program as rows are the labor (male and female), cash, and fertilizer requirements for the activity, as well as any income generated by the activity. The household’s nutritional and cash requirements as well as the household’s labor constraints are put into the model in a column at the end. Using these household requirements and constraints, and each activity’s requirements and benefits, the program chooses the most economical combination of crops and activities for the household as its individual farming and livelihood system. Due to the huge diversity in smallholder farming and livelihood systems, each linear program typically has hundreds of such columns and rows; yet it is easily solved by the optimizing command in a QPRO or Excel spreadsheet. In simulating a household’s farming and livelihood system, the initial goal is for maize as our example of a new technology, however, to make the point that even with this change, food self-sufficiency for this land-scarce FHH is not achieved. 4 This calculation is made using Benson’s (1997) national nitrogen fertilizer response function in 1995/96, a year of good rainfall. In years of drought and poor harvest, the situation worsens. 184 C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 the model to reflect — or model as closely as possible — the current crop mix and allocation of resources of an individual farm household 5. Later, after the model “predicts” the crop choice and cash and labor allocation of the household, the model is confronted with changes in prices, technologies, or other conditions (such as a shock to the system in the form of a severe devaluation of the currency), and is then asked to “adapt” to these changes by being asked “what if” questions. For example, the model may be tested to answer the questions, “What if, after the devaluation, this household starts growing a cash crop?” or “What if the woman spends more time on non-farm income generating activities?” The model’s choice of livelihood strategies (new crops, technologies, or activities) under the new conditions should show which livelihood strategies are more adaptive in the sense of adding to the farmer’s disposable cash income (and thus food security). To illustrate this, we use Anderson’s (2000) results of modeling the livelihood system of Ella, a FHH in Malusa, Zomba, Malawi, who heads a chronically food-insecure household, to see which of the following livelihood strategies are beneficial or adaptive: a tobacco loan option, or more paid farm labor in the form of piece work (ganyu), or a maize safety net (50 kg maize), or a fertilizer safety net (25 kg fertilizer). Ella is the head of a very poor household in the Zomba region of Southern Malawi. She lives with a 22-year old brother, a 17-year old son, and two daughters, 2- and 7-years old. Her brother and son are both in school and only help on the farm after school in the afternoons and on the weekends. Her two daughters are too young to help on the farm, but the oldest attends school and helps with some household chores. Ella owns 0.2 ha of land which she farms. She plants half her land in local maize and half in hybrid maize, but is unable to afford any fertilizer for her field. Intercropped in the maize here and there throughout the garden, she plants cassava, groundnuts, beans, and pigeon peas (called relishes, a term used to indicate a side dish eaten with nsima, the main stable food made from maize). The pigeon peas are planted in the same holes as the maize, but the rest of the crops are planted between the maize stalks. Ella has very low maize yields, due to poor soils and the lack of fertilizer use. In 1998, she did not harvest much if any maize and was forced to buy her maize for most of the year. Her household is certainly chronically food insecure: as shown later, even using fertilized hybrid maize, she is not able to grow enough maize to last the entire year. Because of this, she would benefit from diversifying her system to include a small cash crop. Added paid farm or off-farm employment, even ganyu

5 The methodology is termed “Ethnographic Linear Programming” to emphasize the synergism resulting from the combination of anthropological and economic research methods, and to distinguish it from previous uses of LP models which did not require the researcher to do ethnographic fieldwork before and during the model-building process (Hildebrand, 2001). With ethnographic LP, the researcher conducts extensive in-depth and repeated interviews with the farmer and elicits information on all the income- generating activities in the household in order to model — as accurately as possible — the complex system of activities and resources and assets in the household. The researcher then builds the LP model on his or her laptop during fieldwork. Obviously, new computer technologies and software have made possible this synthesis of old anthropological and economic research methods. C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 185 labor, would help as well. Her household receives its main cash income from the sale of firewood which Ella, her son, and her brother gather from the mountains and sell in the market or to their neighbors. Before the August, 1998 devaluation of the Kwacha (from K27 to K44 per US$1), they earned ca K220 (US$8) each month with this activity. They also sold some cassava for cash as needed. Apart from food, their household expenses, including items such as salt, soap, sugar, matches, paraffin, and clothing, were about K75 (US$3) each month. They require a 50 kg bag of maize each month for consumption6, which if purchased costs K195 (US$7). Obvi- ously, there is a very small margin between their income and expenses. The initial simulation of Ella’s household should reflect her actual farming system in summer 1998, pre-devaluation. It should therefore show her growing 0.2 ha of unfertilized and local maize with cassava, groundnuts, beans, and pigeon peas intercropped with the maize. If the model reflects what is actually happening, it shows that the numbers used for constraints and requirements are probably correct. In these models, the intercrop options available all include cassava, groundnuts, beans, and pigeon peas, a choice of using hybrid or local maize (or both), and a choice of 0, 10, 20, 40, or 60 kg nitrogen applied for local maize or a choice of 10, 20, 40, or 60 kg nitrogen applied for hybrid maize (nitrogen in the form of CAN fertilizer which contains ca 20% nitrogen). Yield data used for Ella in the linear program were collected during interviews with Ella and other nearly-landless FHHs in Malusa, Zomba, in July 1998 (Table 2). These yields are very low when compared to Benson’s (1997) on-farm trial data, but they agree with other estimates for extremely degraded soils (Carr, personal communication). They may be low due to years of farming without the addition of any fertilizer or manure or crop rotation.

Table 2 Yields for hybrid and local maize, used for Ella

N added (kg) Hybrid yield (kg/ha) Local yield (kg/ha)

0–a 120 10 416 279 20 456 396 40 761 506 60 1365 450

a No farmers were interviewed who grew unfertilized hybrid maize.

6 According to FAO requirements, this household needs almost twice as much maize than this. How- ever, the FAO ﬁgures are probably high for most African families, and Ella would not be able to secure this much maize each month, so the program used 50 kg per month as this household’s requirement for maize. 186 C.H. Gladwin et al. / Food Policy 26 (2001) 177–207

Linear programming results

The ﬁrst simulation of Ella’s household, with some results summarized in Table 3, is as expected and reﬂects pretty accurately what Ella actually does. An intercrop of unfertilized local maize, cassava, groundnuts, beans, and pigeon peas was selected to be grown on all 0.2 ha of her land. The model predicts the household should eat all the maize grown and a portion of the other crops grown. The remaining intercropped relish crops are sold. The household must buy 480 kg of maize to sup- plement the maize grown. The cash income for this solution is a realistic amount. The simulation is different from Ella’s actual livelihood system in that the model chooses to use only local maize in the intercrop, while Ella uses both hybrid and local maize. This may be due to the fact that in the model, growing hybrid maize requires cash input for the seeds, and she may actually be “borrowing” those seeds from a family member or friend.

Simulation 2 at post-devaluation prices

After devaluation of the Kwacha, maize and fertilizer prices increased drastically by ca 60%. The maize price increased from K3.9 per kg to K6.5 per kg, while the cheaper and most commonly used fertilizer (CAN) went from K8.9 per kg to K14 per kg. To complete the simulation with the post-devaluation prices, prices of other inputs such as hybrid seed were increased by 60%, and the relish prices and the price for selling ﬁrewood were increased by 30%. The relish and ﬁrewood prices were not increased further, because these items are being sold to other villagers who have also been hurt by the devaluation, and they would not be able to pay a 40– 60% price increase. The 30% mark-up may actually be an optimistic number. Table 4 shows the pre- and post-devaluation prices used; while Table 5 shows Ella’s new livelihood system. With the new post-devaluation prices, Ella plants only 0.083 ha as an intercrop of unfertilized local maize with relish crops of cassava, groundnuts, beans, and pigeon peas. She harvests only 10 kg of maize, and so will have to buy 525 kg of maize in the next year. This solution is infeasible, meaning that with Ella’s current

Table 3 Ella’s livelihood system at pre-devaluation (July 1998) prices

Ha grown kg eaten kg sold Kwacha US$

Local intercropa 0.2 24 Groundnuts 25 41 Beans 25 35 Pigeon peas 17 23 Cassava 80 Yearly cash balance 1115 41

a Intercrop chosen includes unfertilized local maize and the relish crops of cassava, groundnuts, beans, and pigeon peas. C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 187

Table 4 Pre- and post-devaluation prices

Pre-devaluation (K) Post-devaluation (K)

Exchange rate 27/US$1 44/US$1 Maize purchase 3.9 6.5 Fertilizer purchase 8.9 14 Hybrid maize inputs 550 880 Groundnut inputs (seed) 150 240 Bean inputs (seed) 150 240 Tobacco inputs 200 320 Maize selling 2.3 3.0 Groundnut selling 10 13 Bean selling 10 13 Pigeon pea selling 5 6.5 Cassava selling 1.5 1.9 Sweet potato selling 1.7 2.2 Cowpea selling 4 5.2 Soya selling 4 5.2 Mucuna selling 0.35 0.45 Tobacco selling 20 26

Table 5 Ella’s livelihood system at post-devaluation prices (no intervention)a

Ha grown Eaten (kg) Sold (kg) Kwachac US$

Local intercropb 0.083 10 Groundnuts 25 2.5 Beans 25 Pigeon peas 17 Cassava 0 Sweet Potatoes 0.117 233 Yearly cash balance 75 1.7

Simulation 3 with a post-devaluation tobacco loan

One way of coping with the devaluation is to diversify the farm to include a high- value cash crop. In the previous simulation, that was done to some extent with sweet 188 C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 potatoes, which did not generate enough income to allow Ella’s household to maintain its livelihood. In this simulation (Table 6), a tobacco loan is introduced as an option for the model to choose. This loan option loans Ella 500 kg of fertilizer per hectare of tobacco, to be repaid in tobacco at 35% interest. A common practice in Malawi, this is done to ensure that Ella does not take out a tobacco loan and then use the fertilizer elsewhere, so she is forced to use at least part of the fertilizer on tobacco. The remaining fertilizer can be used on tobacco or another crop. This simulation chooses to grow 0.07 ha of tobacco, and after paying back the loan, sells 16 kg of tobacco. Ella does not use all the fertilizer from her loan on the tobacco, but uses part of it to grow 0.13 ha of hybrid maize with 60 kg/ha nitrogen applied to it. Her relish crops are now intercropped with higher-yielding hybrid maize, which increases her yields to 177 kg, so that she only has to buy 335 kg more for the year. The tobacco loan thus allows Ella to maintain her livelihood even after the devaluation. She ends the year with K1364 (US$31), which is still less than her yearly cash income before devaluation (US$41), but does allow her to support her household for the year.

Simulation 4 with a farm employment (ganyu) option

An option for paid farm employment is now introduced (Table 7). It pays K3.0 (US$0.07) per hour worked and is limited to 25 h per month. The limit is because of the lack of available piece work (ganyu) in the villages. Ella now puts all her land into her intercrop of unfertilized local maize, cassava, groundnuts, and pigeon peas. She harvests 24 kg of maize and buys 480 kg of maize. She still sells the relish that is not eaten. The model chooses the farm employment option for the maximum 25 h each month. This employment option helps Ella immensely. She is able to maintain her livelihood and has K1748 (US$40) at the end of the year. This is more cash than she received with the tobacco loan (US$31), and is very close to what she earned before the devaluation (US$41). However, her own maize pro-

Table 6 Ella with a tobacco loan at post-devaluation prices

Ha grown Eaten (kg) Sold (kg) Kwachab US$

Hybrid intercropa 0.13 177 Groundnuts 25 18 Beans 25 14 Pigeon peas 17 9 Cassava 52 Tobacco 0.07 16 Yearly cash balance 1364 31

a Intercrop chosen includes hybrid maize with 60 kg/ha N applied, cassava, groundnuts, beans, and pigeon peas. b Kwacha in this model are devalued, K44 to US$1. C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 189

Table 7 Ella with a paid farm labor option (25 h/month)

Ha grown Eaten (kg) Sold (kg) Kwachab US$

Local intercropa 0.2 24 Groundnuts 25 41 Beans 25 35 Pigeon peas 17 23 Cassava 80 Yearly cash balance 1748 40

a Intercrop chosen includes unfertilized local maize, cassava, groundnuts, beans, and pigeon peas. b Kwacha in this model are devalued, K44 to US$1. duction is again drastically decreased, because she once again grows unfertilized local maize, lacking the credit for fertilizer from the tobacco loan.

Simulation 5 with a maize safety net

The program now introduces food relief in the form of a maize safety net that gives 50 kg of maize to FHHs such as Ella (via a supplementary feeding program) to help her household through the hungry season (Table 8). Ella now plants 0.107 ha in an intercrop of unfertilized local maize and her relishes. She harvests 13 kg of maize and with the 50-kg maize safety net, she still has a consumption deﬁcit of 455 kg of maize. She puts the remainder of her land, 0.09 ha, into sweet potatoes that she sells. The maize safety net now allows the simulation to reach a solution, compared to the infeasible solution reached with post devaluation prices and no intervention, and she has K534 (US$12) for a yearly cash income, less than the income for both the tobacco (US$31) and paid farm labor (US$40) options.

Table 8 Ella with a 50-kg maize safety net

Ha grown Eaten (kg) Sold (kg) Kwachab US$

Local intercropa 0.107 13 Hybrid maize (from safety 50 net) Groundnuts 25 10 Beans 25 7 Pigeon peas 17 5 Cassava 43 Sweet potatoes 0.09 185 Yearly cash balance 534 12

a Intercrop chosen includes unfertilized local maize, cassava, groundnuts, beans, and pigeon peas. b Kwacha in this model are devalued, K44 to US$1. 190 C.H. Gladwin et al. / Food Policy 26 (2001) 177–207

Simulation 6 with a fertilizer safety net

Now the program introduces a fertilizer safety net of 25 kg of fertilizer which is approximately the same cash value as the 50 kg of maize used in the maize safety net option. With a fertilizer safety net, the model chooses to put a very small amount of the fertilizer on tobacco (0.004 ha), and sells 4 kg of it. The rest of the fertilizer is put on 0.076 ha of hybrid maize with relish intercropped and with 60 kg/ha N applied. Ella also grows 0.119 ha of a local maize intercrop, and thus harvests 104 kg of hybrid and 14 kg of local maize. The total maize yield is 118 kg, requiring Ella to purchase 380 kg of maize. The fertilizer safety net, like the maize safety net, brings Ella from an infeasible solution to a feasible one. However, the fertilizer safety net provides her with more harvested maize and more cash, US$21 more, than the maize safety net. If the objective is to maximize disposable cash income or minimize maize that is purchased, the fertilizer safety net is a better choice than the maize safety net as the vehicle for food relief (Table 9).

Simulation 7: selling the fertilizer grant

One concern that has been raised in the safety-net debates in Malawi is that farmers may sell the fertilizer given to them as a safety net, rather than apply it to their food crops. For example, some of the fertilizer starter packs that were distributed in Malawi in 1999 were sold by farmers who desperately needed the cash (Longley et al., 1999). The problem is that they were selling the 25 kg packs for US$0.35 and $2.30 (between K15 and K100), when they were worth US$8.00 (K350). To see the impacts of this activity, we forced the model to sell the 25-kg of fertilizer for K100 (Table 10). Because Ella sells all the fertilizer from her grant for K100 (US$2.30), she now

Table 9 Ella with a 25-kg fertilizer safety net

Ha grown Eaten (kg) Sold (kg) Kwachac US$

Local maize intercropa 0.119 14 Hybrid maize intercropb 0.076 104 Groundnuts 25 39 Beans 25 34 Pigeon peas 17 22 Cassava 78 Tobacco 0.004 4 Yearly cash balance 1459 33

a Local intercrop included unfertilized local, cassava, groundnuts, beans, and pigeon peas. b Hybrid intercrop included hybrid maize with 60 kg/ha N applied, cassava, groundnuts, beans, and pigeon peas. c Kwacha in this model are devalued, K44 to US$1. C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 191

Table 10 Ella, selling the 25-kg fertilizer granta

Ha grown Eaten (kg) Sold (kg) Kwachad US$

Local intercropb 0.06 7 Hybrid intercropc 0.02 27 Groundnuts 25 25 Beans 25 Pigeon peas 17 Cassava 0 Sweet potatoes 0.12 233 Yearly cash balance 75 1.7

a This solution was infeasible, meaning that there was no possible solution given the existing constraints. This solution was K269 (US$6) short of being feasible. b Intercrop chosen includes unfertilized local maize, cassava, groundnuts, beans, and pigeon peas. c Hybrid intercrop includes hybrid maize with 60 kg/ha N applied, cassava, groundnuts, beans, and pigeon peas. d Kwacha in this model are devalued, K44 to US$1. has to decrease the amount of the hybrid maize intercrop planted (from 0.08 to 0.02 ha), and ends up harvesting only 34 kg maize, leaving her a consumption deficit of 495 kg for rest of the year. She plants sweet potatoes on the rest of her land (0.12 ha) and sells it. The hybrid maize was selected in order to try to fulfill the household’s food needs, however, and she did not actually have the money to purchase the fertilizer for this maize. The solution is K97 (US$2.20) short of being feasible, meaning she again cannot fulfill her household’s food and cash needs, and so her livelihood system is again unsustainable. Use of LP simulation models of livelihood systems of women farmers can therefore show the impact of different policy interventions on women farmers and their households, and in fact provide some way to measure if a household’s livelihood strategy is adaptive (and beneficial to the farmer) or non-adaptive (and erosive). In the example of Ella, the LP results show that poor land-scarce FHHs growing only subsistence crops cannot adapt to a sudden shock — such as a severe devaluation of the currency — without subsequent interventions in the form of the introduction of a cash crop with credit, or more paid employment, or food relief in the form of a maize- or fertilizer-safety net. Inter-household linkages thus have a major influence on decision making, particularly for the poorer FHH who is in a more dependent position within the lineage group. Without any intervention, such a FHH is not able to sustain her livelihood, and this is reflected by the fact that the LP solutions in simulations 2 and 7 (Tables 5 and 10) are infeasible. Of the feasible solutions (and adaptive livelihood strategies), the maize safety net would not be as beneficial as the others, as measured by Ella’s yearly cash income; and selling the fertilizer safety net does prove to be an erosive livelihood strategy, as expected. The most beneficial strategies to FHHs include more paid farm employment, a fertilizer safety net, and the introduction of a cash crop with credit. Note that with the latter option of growing 192 C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 tobacco-with-credit, Ella is also able to grow higher-yielding hybrid maize which increases her own food production seven-fold. Although the shock to the livelihood system in our example was in the form of a currency devaluation, it could just have easily been in the form of a drought or heavy rain, also common occurrences in southern Africa of late. Seasonal shocks such as these have a major influence on agriculturally-based outcomes, are very difficult to predict in advance, and imply that the issue of timing is crucial in terms of who benefits and who loses out. Poverty can thus be seen as the outcome of rural competition for scarce resources (land, labor at key times, knowledge, and access to inputs).

Why multiple livelihood strategies work for women farmers

Given these simulation results, we now turn to evidence that African women farmers, married women in MHHs as well as women in FHHs, recognize the importance of multiple livelihood strategies to their food security. Such evidence comes from Peters’ work which shows that particularly where drought or pest attacks can have a major effect on food security, the households whose members have multiple sources of income are best off (Peters 1992, 1993). For African women, combining farm and non-farm income-earning activities has long been an adaptive strategy which allows them to reduce the risk of starvation for themselves and their families during periods of chronic or transitory food insecurity (Devereux 1993, 1999; Maxwell and Frankenburger, 1992). To be food secure, women must have multiple livelihood strategies, and they recognize this fact. The reason for this is that none of the strategies on their own are capable of sustaining them. In Africa as in other parts of the world, therefore, women farmers are also petty traders, food processors, and engage in informal labor markets (Pearce et al., 1996). Evidence for multiple livelihood strategies also comes from our work in the ICRAF/World Vision/University of Florida Soils CRSP project in Eastern Zambia, where Peterson (1999) found that few farmers in the project area had formal non- farm sources of income7. It was more common for farmers to have children or family members in town who sporadically assisted with cash and goods than to have household members with formal off-farm employment. Yet she also found a total of 25 different income generating activities (listed in Table 11) performed by farmers. Farmers generally categorized these activities as “small money” activities, “medium- sized money” activities, and “big money” activities. Women’s small money activities included activities such as selling buns or fritters, sewing, selling sugar cane or bananas, buying and reselling oil and other items from town, and piece work (ganyu); the income was usually used for grinding maize and purchasing soap and salt. The

7 Peterson (1999) intervewed 121 farmers (81 women, 40 men) in four villages around Chipata, Eastern Zambia, as part of a study of women’s and men’s adoption of improved fallow technology undertaken collaboratively by the International Centre for Agroforestry Research (ICRAF), the University of Florida’s Soils CRSP (collaborative research support program), and the Zambian Ministry of Agriculture, Food and Fisheries. C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 193

Table 11 Women’s and men’s income generating activities in Eastern Zambia (n=121)

Income generating activity Number of women Number of men (n=81) (n=40)

Selling crops such as cotton, maize, 40 24 groundnuts, potatoes, beans, tobacco, soybeans, sunflower seeds, bananas, sugar cane or vegetables (rape, cabbage, tomatoes) Selling cotton 36 17 Performing ganyu (piece work) 30 7 Gardening (bananas, sugar cane, vegetables) 23 19 Brewing beer 23 0 Selling animals (cattle, pigs, chickens, goats) 22 17 Buying and selling oil, paraffin, sugar, 16 4 cigarettes, soap, or sweets Selling buns or fritters 11 0 Regular employment such as teachers, health 4 3 workers or farm laborers on large commercial farms Remittances from children who work in town 4 1 Making pots 4 0 Exchanging maize for kapenta, and selling 3 3 kapenta Pressing sunflower seeds into oil to sell 3 3 Sewing and knitting 2 0 Being a traditional healer 1 0 Temporary work repairing feeder roads 1 0 Selling grass for thatching 1 0 Rent homes in town (if retired to village) 2 0 income from “medium sized” money activities such as gardening, brewing beer, selling goats, chickens or pigs, or selling crops such as sweet potatoes, soybeans, sunflower and groundnuts, on the other hand, was used for school fees and medical expenses. In contrast, the income from “big money” activities such as producing cotton or tobacco allowed farmers to purchase luxury items such as clothes, blankets, and shoes, to invest in livestock, and to purchase fertilizer for the following year. Peterson also found evidence of bartering activity. In order to acquire maize, farmers often bartered their own labor or sold commodities such as vegetables, salt, meat or fish. Labor, commonly bartered for maize, was in the form of piece work to build houses, repair roofs, cut thatch, build granaries, or plow, weed or harvest fields. For example, in 1998 one woman farmer used a goat to pay school fees and purchase uniforms, used gardening income to purchase daily household needs, sold cotton to buy fertilizer for maize, and performed piece work in exchange for maize. She also sold groundnuts to purchase items such as oil, soap and salt to sell locally. Another farmer used income from cotton to purchase kapenta, beans, soap and sugar to exchange locally for maize. One farmer actually sold an entire cow to acquire enough maize for his family. 194 C.H. Gladwin et al. / Food Policy 26 (2001) 177–207

Clearly, this evidence shows that agricultural production is the basis of most households’ source of income, but not their only source of income. Women especially are engaged in alternative cash-generating activities for securing food, including beer brewing, sale of snack foods, vegetable production and processing and selling, performing ganyu (piece work), and petty trading. Men also are engaged in informal income generating activities. In addition to the activities listed in Table 11, men in this sample rented out oxen for plowing (n=5), made bricks (2), built homes (2), sold firewood (2), owned small shops (2), bought items in the village to trade in Malawi (2), purchased dried fish in Malawi to sell in Chipata, Zambia, or exchange for maize in the village (2), fixed bicycles (1), repaired shoes (1), and sold milk in town (2). There is thus good evidence that African rural households have some cash income with which they buy or barter for food, although it tends to be in the form of informal income-generating activities, many of which are “small money” and “medium money” activities, rather than more formal off-farm employment. For example, only half the women — and little more than half the men — in this sample reported selling crops, a “big money” activity used to buy fertilizer, clothes, livestock. The question remains whether in time these informal income-generating activities can be expanded in scope to provide more income for food-insecure rural women, and how long this will take. We return to this question below.

Impacts of multiple livelihood strategies on women’s food production

Another reason for African policy analysts to encourage and facilitate multiple livelihood strategies of women farmers is that they may be the only sustainable way African women farmers can pay for Green-Revolution inputs of production like fertilizer on their food crops. Ironically, women’s cash cropping may be one of the only ways to increase their food production — and thus aggregate food production in Africa. The reason for this is historically based in the structural adjustment programs (SAPs) of the 1980s. Structural adjustment programs, known as SAPs in Africa and “neoliberal policies” in Latin America, were measures designed to end the economic crises which followed the oil price hikes of the 1970s8. The aim of structural adjustment loans (SALs) from the World Bank and bilateral donors was to stabilize ﬁscal and monetary policies and remove price distortions which lead to

8 The oil price hikes of 1973 and 1979 as well as other “internal” factors plunged most developing countries, but especially those in sub-Saharan Africa and Latin America, into trade imbalances and mass- ive snowballing debt in the 1970s and 1980s. To help developing countries cope with financial strangu- lation, the curtailment of foreign exchange, and increasing interest payments, during the 1980s the Inter- national Monetary Fund (IMF) and the World Bank as well as bilateral donors (e.g., USAID) stepped in and changed the direction of their lending from project-oriented funds to conditional funds. Basically, they provided needed capital infusions if countries agreed to undertake needed structural reforms: devaluation of overvalued curriencies, increases in artificially-low food prices and interest rates, a closer align- ment of domestic prices with world prices, an emphasis on tradeables/exportables and trade liberalization, privatization of government parastatals, wage and hiring freezes in the public sector, removal of food and input subsidies, and reductions in budget deficits (ECA, 1989: 18–20). C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 195 misallocation of resources and ultimately stagnation of the economy as a whole; proponents defended structural adjustment policies by claiming that without some form of adjustment, the situation in most Third World countries would have been far worse (Lele, 1990). Unfortunately, structural adjustment policies also included removal of all input subsidies on fertilizer, credit, and irrigation that many economists (Eicher, 1995; Lele et al., 1989; Gladwin, 1992) claimed were responsible for Green-Revolution increases in yields in Asia and Latin America but are now not allowed in Africa. When these subsidies were removed, it was inevitable that input prices would increase and in particular prices of fertilizer, most of which was imported, would increase. During the late 1980s, these prices increased slowly because fertilizer stocks were still held in many countries. During the 1990s, however, fertilizer prices in Africa increased rapidly, due more to devaluations of the local currency than to the lagged effect of fertilizer subsidy removal (Bumb et al., 1996). In Malawi, for example, the final removal of all fertilizer subsidies in 1995/96, coupled with a 100% devaluation of the kwacha in 1994, meant 200% to 300% increases in the price of fertilizer without corresponding increases in maize prices in 1995/96 and 1996/97 (Benson, 1997). Similarly in Ghana, fertilizer prices increased slowly in the late 1980s, then more rapidly in the 1990s, more due to the recurrent devaluations of the cedi in 1982, 1989, 1995 and 1996, than to the lagged effect of fertilizer subsidy removal in 1990 (Bumb et al., 1996). From 1996/97 to the present day, only very small amounts of chemical fertilizer, alone or in combination with organic sources of nutrients, are now profitable for food crop production, especially maize production (Kumwenda et al., 1996; Jama et al., 1997; Bumb et al., 1996; Benson, 1997). The current adverse price ratio of fertilizer to food crops means that in Western Kenya, organic and inorganic fertilizers are not now profitable on maize, but are on tomatoes (Buresh and Niang, 1997). In Ghana, Bumb et al. (1996) claim fertilizer on maize is not profitable. In Mali, however, Sanders (1997) shows fertilizer was profitable on maize in 1996, even after a 100% devaluation in the CFA countries in 1994 led to a 70% increase in the maize- fertilizer price. In Malawi, data analyzed from nitrogen (N) fertilizer response functions estimated nationally by Benson (1997) with data from 1600 on-farm trials on hybrid maize show the answer partly depends on whether one assumes farmers are perfect profit maximizers or merely satisfiers. Perfect profit-maximizers who exactly equate the value of the marginal product (VMP) to marginal cost (MC) find some fertilizer use profitable; satisfiers or the risk-averse who use the rule of 2 (i.e., VMP has to be at least twice the MC) find fertilizer profitable only in very small amounts. The numbers also depend on whether one uses consumer or producer prices in the calculation, as consumer prices are often 1.5 times that of producer prices. Benson in Malawi thus finds 69 kg N profitable for hybrid maize consumed at home, but only 35 kg N is profitable for hybrid maize produced for sale9.

9 It is still cheaper, even at current price ratios, for a maize farmer whose own labor is costless to her 196 C.H. Gladwin et al. / Food Policy 26 (2001) 177–207

What’s the problem? Gender-division-of-labor rules in Malawi dictate that women usually grow the maize for home consumption, and their lack of cash and credit block their use of fertilizer so they end up planting unfertilized local maize intercrops (or local-hybrid maize intercrops as Ella did); while men with greater access to cash and credit plant hybrid maize as a cash crop (Gladwin, 1992). As a result, with the recent increases in fertilizer prices, men decreased the area planted to hybrid maize (a cash crop for them) from 24% of the total maize area in 1992 to 7% in 1996, same as that of 15 years ago (Carr, 1997). This was contrary to Smale’s (1995) optimistic prediction that it would increase to 40% of the total maize area with “Malawi’s delayed Green Revolution”. Clearly, some way has to be found out of this impasse, and interventions which facilitate women’s cash-generating activities would seem to be a logical way for them to acquire modern yield-increasing inputs of production like fertilizer.

Constraints to immediate expansion of women’s cash income

African policy planners need to look at ways of improving returns to women farmers’ resources in a broader context than a narrow focus on their food production allows. They should instead look at opportunities to increase their cash cropping, agricultural labor, and off-farm income-earning activities. Yet rural women face powerful constraints which now prevent them from generating much if any cash income. It is questionable whether policy planners can alleviate these constraints soon, because these constraints are so deeply ingrained in the cultural and economic fabric of African societies that they are more appropriately described as characteristics of African peasant economies. The first is the time period needed by rural women to get formal non-farm sources of income will be necessarily long in Africa, as it would be in any country at the early stages of structural transformation, when manufacturing and service sectors are not mature or diverse enough to absorb significant increases in the labor force. Second, African women tend to define themselves by their roles and social identities as the food providers in the household. Third, the decision logic of land-scarce farmers inadvertently leads them to plant subsistence crops before most cash crops. We discuss each of these propositions in turn, and conclude with their implications for short-run vs long-run agricultural change.

Time to adjustment

Given that we need to look at ways of improving returns to women farmers’ resources in a broader context than a narrow focus on their food production allows, the question remains: how much adjustment time are we talking about? Tomich et

to buy fertilizer and produce her own maize for home consumption than it is to buy it from a private or public trader (Hildebrand, personal communication). C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 197 al. (1995: 14) estimate the time it will take to diversify an economy at the early stages of structural transformation, when it is mostly dependent on agriculture, to one with developed agricultural, manufacturing, and service sectors, to be quite long. The time required for a CARL (country with abundant rural labor) to transform and diversify its economic structure is called the “structural transformation turning point”, defined as the point in time when the absolute size of the agricultural labor force peaks and begins to decline. For African countries, which comprise most of the 58 countries now identified as CARLs (Tomich et al. (1995: Table 1), this is an extremely important consideration because their high population growth rates, rang- ing from 2.5 to 4% per year, impede their reaching the structural transformation turning point — when the economy begins to diversify — any time soon. For example, for countries with population growth rates of 3.3% per year and 75–80% of the labor force still in agriculture, they estimate that the time period required for structural transformation ranges from 32 to 58 years, even given the most optimistic (5–6%) rates of growth of labor absorption from the agricultural into the non-agricultural sectors. Unfortunately, given these high population growth rates, the non-agricultural labor force cannot absorb enough of the total labor force to quickly decrease the size of the rural sector dependent on agriculture for its income. If the diversification of the economy takes this long, how realistic is it that rural women can acquire off-farm employment and thus significantly expand the scope of their non-farm income-earning activities quickly? Not very. Women farmers will need at least this amount of time to acquire more formal off-farm employment than the informal income generating activities seen in Table 11, because they are the least educated and the least connected to powerful people with non-farm jobs in town10. African rural women will therefore have to rely on the more informal income-generating activities — the “small money” and “medium money” activities — to generate their cash income for a significant period of time. During this time period, women without “big money” activities (such as selling cash crops) will need a safety net or program to give them public assistance. Safety nets imply a process of moving from government programs which are open to all, regardless of income level, to programs where eligibility is related to poverty and the level of benefits is related to the level of poverty (Deaton, 1980; Bezuneh et al., 1988). We return to this topic in the con- clusions.

Women’s roles and social identities

Powerful ideological constraints and barriers limit women’s economic opportunity sets. In most parts of Africa, women consider farming for food as part of what makes them women and gives them a gender identity. The cultural categories of gender in

10 This length of time is also required for a country to develop strong reliable markets and a distribution system in food crops that rural people can depend on, as well as the physical and governmental infrastructure to support them. One year of poor harvests and no food crops in the markets is all it takes for conﬁdence in the markets, infrastructure, and government to plummet. In the following seasons, women will decrease cash crop production and revert to subsistence farming. 198 C.H. Gladwin et al. / Food Policy 26 (2001) 177–207

Africa today usually link farming-female-food as a gender marker (Goheen 1991: 240). The analogy in Europe and the Americas is that women consider the cooking of food to be feminine and to define them as women, such that “A good woman is a good cook” is a norm many women learn during childhood when gender identities are first formed. In contrast, African rural women define themselves by their ability to wield a hoe and grow as well as cook the food for the household. For them, “A good woman is a good food farmer”. Unfortunately, as Goheen (1991, 1996) points out for the case of Cameroon, ideology regarding gender categories has been a primary stumbling block to women’s access to resources, particularly to land. The designation of women as primary food farmers and providers used to encourage a relative equality and complementarity between male and female qualities (Kaberry, 1952); but with changing material conditions the complementary roles played by men and women have become much less equal. “The contradictions in women’s role as primary food farmers have deepened, and there is now evident a ‘feminization of poverty’” (Goheen 1991: 241), partly because government has institutionalized these cultural constraints and created socio- legal constraints and barriers for women farmers. Whereas previously, custom alone dictated that “men owned the land, women begged for it”, now government policies under the pretext of land reform has put up so many hurdles for new land acquisition that only the urban elites and “big men” can jump them and invest in land, leaving rural women on very small landholdings. Another barrier for women is that cash crops (and income-earning activities in general) are seen as part of the male domain; while only subsistence food crops, not sold but consumed in the household, are in the female domain. In Africa, this means the (women) food producers usually do not have access to cash from the sale of cash crops with which to buy yield-increasing inputs (Due and Gladwin, 1991); and they are dependent on their husbands or sons to buy them fertilizer. In Malawi, however, wives of tobacco farmers claim that their husbands buy them a couple of dresses and keep the rest of the additional income from tobacco, irrespective of the amount of labor provided by the women. In Dowa, Malawi, where the NGO VEZA/HODESA has a program directed at women only, project staff report that their husbands decide if and how much credit (repaid in bags of hybrid maize harvested by both men and women) is repaid to the program, because hybrid maize is considered a cash crop and therefore part of the male domain (D’Arcy, 1998).

The decision logic of land-scarce farmers

There are other reasons why African women farmers might not readily diversify their cropping patterns and switch into cash crops. Evidence from other land-scarce countries (e.g., Guatemala in Central America) shows that land-scarce farmers there do not prefer cash crops to subsistence crops unless the cash crops are twice or thrice as profitable as subsistence maize. Results of testing a cropping decision model in several agroclimatic zones of the Highlands of Guatemala, where average amount of land cultivated is 0.36 ha in some regions (e.g., Almolonga, Totonicapan), show that only 37% of farmers consider the cash crop more important than subsistence C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 199 maize and plant it first, before maize; 63% farmers consider the family’s consumption needs first, before deciding whether or not to plant a cash crop (Gladwin, 1983). The cash crops that take priority over maize are usually more than twice as profitable as maize, for example, coffee, fruit trees, and irrigated vegetables; but only a few regions of the Highlands have the climate, irrigation, or market necessary for these crops. With the more common, not-so-profitable cash crops (e.g., rainfed wheat, potatoes, and vegetables in Guatemala), farmers plant subsistence crops before cash crops, in part because they don’t trust the markets to be reliable, in part because they don’t trust themselves to have the cash when needed (Gladwin, 1983). To encourage these farmers to diversify their crop mix and thus increase their incomes, policy planners at ICTA (the Guatemalan Institute of Agricultural Science and Technology) in the 1970s promoted intensification of maize production in the form of improved maize varieties and fertilizer use on the subsistence crop maize. Farmers who could not adopt higher-yielding varieties tended to plant more land to subsistence maize and less land to cash crops. Data from Malawi in 1997 suggest that it is no exception to this rule. Since liberalization of maize and fertilizer markets, more local maize and less hybrid maize is being planted: Carr (1997) reports that the area planted to (fertilized) hybrid maize has not increased to 40% of total maize area as predicted by Smale’s “delayed revolution” (1995), but has decreased from 24% of the total maize area in 1992 to 7% in 1996, same as that of 15 years ago (Carr, 1997).

In conclusion: a four-pronged sustainable strategy The current thinking about food security, that it is an issue of household income and poverty and not just aggregate food production, challenges programs focusing only on women’s food crop production. It suggests that different developmental interventions, both in policy and in technology, are needed to address the food insecurity of women farmers. What is needed as a general rule are interventions to increase women’s incomes and help make their livelihoods sustainable. Yet the particular form these interventions will take should vary depending on the assets and household composition of the women being targeted: in many societies, women in FHHs and MHHs cannot be treated as a homogeneous group; and younger women with high demands on their labor cannot be treated like older women with more adult labor (and cash income) available. Given the complexity of women’s multiple livelihood systems, we also conclude that cash and food crop production by African women farmers are so interdependent that it is almost impossible to separate them. The intensiﬁcation of food production by women farmers requires them to also grow cash crops which traditionally have been in the male domain; while their ability to switch some land out of food crops into cash crops requires them to intensify their food production. Based on these interdependencies, rather than simply recommend an increased use of chemical fertilizer to expand the aggregate food supply (Larson and Frisvold, 1996), we recommend a more complex strategy with four interrelated parts: 200 C.H. Gladwin et al. / Food Policy 26 (2001) 177–207

(1) Encourage women’s income generating activities and multiple livelihood strategies, including cash cropping of very profitable cash crops, non-farm microenterprises, and agricultural labor that will bring in cash to women in the household. Cash cropping on a small portion of women’s land normally devoted to the subsistence crop(s) can be encouraged by women’s clubs such as Malawi’s Tikalore Clubs or women’s tobacco clubs which give credit to women for fertilizer for both food and cash crops, to be repaid from proceeds of the cash crop. Note that credit programs for fertilizer for food crops alone should not be recommended at adverse price ratios of fertilizer to food crops, because their use will only get women farmers involved in a negative debt spiral. However, when women get fertilizer under credit schemes intended to improve cash cropping, they should be free to decide to which crops they apply the fertilizer, as farmers are often better judges of the markets and risks than are outside analysts. Government can encourage women’s earning cash income by expanding microcredit and microenterprise programs for women which allow them to acquire credit for whatever income-earning activity they desire, that is, a farm or non-farm enterprise. All these programs should recognize the interdependencies between women’s cash-generating activities and the simultaneous need to intensify their food production. For example, the women’s group that encourages and facilitates women to produce handicrafts for sale over the web might also sell fertilizer by the kilogram to its members. (2) Complement (1) with agricultural research programs aimed at increasing women’s returns to their land as part of the overall package in (1), but not to have women expend more calories and labor than comes out in terms of increased food yields. The goal here is to increase agricultural productivity while taking into account the diversity of livelihood systems employed by women farmers (Gladwin et al., 1997, 1999). Clearly, Africa can benefit from the high returns to agricultural research that currently benefit the rest of the world (Roseboom and Pardey, 1996); and the challenge remains for agricultural researchers to design technologies that women farmers can afford to adopt. Unfortunately, due to women’s severe cash and credit constraints, they cannot adopt high-cost technologies using high amounts of chemical fertilizer, and are therefore bypassed — and further marginalized — by some of the country programs of Sasakawa Global 2000 as they are currently implemented (Gladwin 1996, 1997). It would be better for some of these programs to conduct on-farm trials with women farmers using combinations of smaller amounts of chemical fertilizer (18 kg/ha instead of 74 kg/ha of nitrogen) coupled with grain legumes intercrops or green manures undersown. Williams’ (1997) work in Western Kenya also shows that labor constraints on women farmers do not allow many of them to adopt some of the agroforestry innovations (hedgerow intercropping and biomass transfer technologies) developed in on-farm trials by the International Center for Research on Agroforestry (ICRAF), the Kenya Agricultural Research Institute (KARI), and the Kenya Forestry Research Institute (KEFRI), because women do not have the labor available to cut and carry 21 tons/ha of fresh biomass11.

11 Williams (1997) used ethnographic interviews and decision tree modeling to elicit from a sample of 40 women farmers in Maseno, Kenya, their reasons for adoption or non-adoption of hedgerow inter- C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 201

Examples of technologies women farmers can adopt include “doubling-up legume” technologies in land-scarce situations (Snapp, 1999) and improved fallow technologies in land-abundant situations. ICRAF on-farm trials of improved fallows with Sesbania sesban rotated with maize are now being conducted with 2900 participating farmers in Eastern Zambia, a region of lower population density than either western Kenya or southern Malawi (Franzel et al., 1997; Kwesiga et al., 1997); and 49% of the participants are women farmers. Peterson’s (1999; Peterson et al., 1999) adoption research shows improved fallow technologies look especially promising for poorer African women farmers in areas of low population density, because they are looking for a substitute for unaffordable chemical fertilizer (Palm et al., 1997). Yet in areas of high population density, women with land, labor, and cash constraints are not likely to substitute agroforestry innovations for nitrogen fertilizers. For them, “doubling-up legumes” technologies may be an answer (Snapp, 1999). Clearly, more biophysical as well as socioeconomic adoption research needs to be done. (3) Realize rural women are not a homogeneous group, and more than one “best- bet” recommendation may be needed. Women in FHHs and MHHs should not be treated as a homogeneous group, especially in societies where cash is considered to be in the male domain. In these societies, women in FHHs might adopt cash crops and new income generating activities more easily than do women in MHHs, even though they tend to have less land and less adult labor. Evidence for this comes from Peterson’s (1999: 52) research in E. Zambia where women in FHHs are more prepared to test ICRAF’s improved fallow technologies than women in MHHs, partly because proportionately more FHHs cannot afford fertilizer now and are looking for other, less-costly soil fertility options. In other societies, household composition may be an additional factor greatly affecting adoption of new livelihood strategies by women. Sullivan’s (2000) LP model of Pulaar women in MHHs in the Casamance region of southern Senegal shows that the younger women with high demands on their labor cannot be treated like older women with more adult labor (and cash income) available. Because of these high labor demands, her model predicts that when hybrid rice seeds and credit

cropping (HIC) technologies; and confirms the earlier work of researchers that it is not being adopted by farmers (David, 1993; Swinkels and Ndufa, 1993; Bekele, 1996; Shepherd et al., 1997; Swinkels and Franzel, 1997). About a third of the women had no knowledge of HIC technology. Other constraints included women’s lack of access to seedlings, a lack of knowledge of how and where to plant them, and the belief that planting trees would actually lower soil fertility. More common, however, were shortage of land and labor constraints, where agricultural intensity and population density were high. Many female heads of households and women with small children felt that the labor required to coppice the trees would prevent them from using this technology. Where hedges were not frequently pruned, some farmers noted that shading of companion crops reduced crop yields. Some farmers who had tried HIC said that the trees were taking up “more room than the crops themselves” and/or were shading them out, so they decided to uproot them. In addition, many women reported problems with pests such as termites eating the seedlings, while a few experienced attacks by the psyllid pest (Heteropsylla cubana) and lacked the cash to buy pesticide. This resulted in a substantial decrease in biomass production, which caused women farmers to want to uproot the trees. The cumulative result of all these constraints was that the decision model predicted only eight of the 40 women should use HIC technologies. 202 C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 for fertilizer are offered women in this region, the younger women with young children will not adopt while the older women with grown children, who have more labor and cash income available, will adopt. (4) In the short run, provide the poorest women farmers with productivity-enhancing safety nets, or PES-nets. Here, the term safety net refers to government programs which attempt to address a food consumption deficit in households of either the chronically poor and food insecure or the transitory food insecure. In cases of chronic food insecurity, safety nets are targeted at the poorest quintile or two (and rarely three), but would thus probably include the majority of FHHs. In Malawi, for example, the poor comprise 41% of rural households, 40% of whom are female- headed. Except in rare cases of severe drought or devaluation, safety nets should not be given universally as were Malawi’s “starter packs” in 1999 and 2000 (Mann, 1998; Longley et al., 1999). Safety net programs, as opposed to subsidies, can be productivity-enhancing programs which work through the markets instead of disrupting them. There are several kinds of safety nets that satisfy this criterion: “food-for-work” programs, public employment programs, “inputs-for-work” programs, and “vouchers-for-work” programs. The advantage of productivity-enhancing safety nets (PES-nets) is that they target the people who are food insecure while at the same time do not detract from the national goal of increasing productivity so that the country as a whole moves forward toward structural transformation. Devereux (1999: 57) points out that when food insecurity is caused by low productivity, as is typically the case in Africa, it is “best addressed by interventions to raise returns to effort” instead of bridging the consumption deficit with food transfers. “Reducing production or income deficits is a pre-emptive strategy to reduce consumption deficits, thereby minimizing the need for safety net interventions”. Safety nets that provide consumption support to people below the poverty line — especially farmers who know how to produce their own food — such as the maize safety net in the example of Section 3, “have no beneficial impact on livelihood systems”, divide the poor into “workers” and “dependents”, are not sustainable, and merely deepen dependency (Devereux, 1999: 57). PES-nets can be in the form of public works programs that will improve the food security of participating households if the time spent on them does not conflict with food production activities. Typically, however, public works programs focus on male tasks, for example, rebuilding roads and bridges and water canals, reforestation projects, and thus hire mostly men. To benefit poor rural women, however, public works programs should also include tasks that women typically do, such as communal gardening and care of communal (agroforestry) nurseries, soil conservation programs, care of the sick or orphans of AIDs (a task usually left to grandmother- FHHs), care of the communal water kiosk, rubbish disposal pit, or soak-away pit. Public works programs could also remunerate men’s and women’s participation in group training sessions about family planning, literacy, and crime prevention. Not only the definition of “work” in “food-for-work” programs needs to be broadened, but also the definition of remuneration-for-work needs to be expanded. Female participation rates are higher (60% vs 20%) when payment is made in food than when cash wages are offered in Malawi’s public works projects (Dil, 1996). C.H. Gladwin et al. / Food Policy 26 (2001) 177–207 203

For women farmers, the most optimal form of PES-net would be fertilizer vouchers received for work in “fertilizer-for-work” programs, as shown in our example of Section 3, because they are more cost-effective than programs offering a food wage and do not deepen dependency. In Malawi, for example, they are more cost-effective because the current nitrogen to hybrid-maize price ratio is now so high that only small amounts of fertilizer (e.g., 37 kg/ha of nitrogen) are still proﬁtable or “optimal” for food production12. At these low levels of fertilizer, however, the response from an additional kilo of nitrogen is high13. This means that the cost of maize to the farmer growing her own maize with fertilizer is much less than the price of maize she would pay to buy maize. Because it costs the farmer much less to buy fertilizer and produce her own maize than to buy maize in the market (especially during the hunger months), a safety net program that gives a fertilizer voucher, redeemable from any private fertilizer distributor, should be more effective than one that exchanges (maize) food for work 14. This is supported by results of Tsoka and Mvula (1999) that show the majority of rural residents in southern Malawi, both FHHs and MHHs, prefer payment on public works in fertilizer ahead of cash or food (43–47% vs 32); of those who did not choose fertilizer, more MHHs named cash rather than food (32% vs 21%), and more FHHs chose food rather than cash (33% vs 23%). “The evidence is overwhelming: the rural poor in Malawi see access to agricultural inputs as a priority, and inputs-for-work for part of the year as a means of obtaining fertilizers and seeds” (Devereux, 1999: 58).

12 Only small amounts of fertilizer (e.g., 32–37 kg/ha of nitrogen from CAN) are still profitable for food production (Benson, 1997). These figures assume the farmer gets no credit for food crops, pays Malawi Kwacha (MK) 700 per 50 kilo bag of CAN, and the price of maize is a high MK 6.5, a four- fold increase from its previous price of MK 1.5 in 1997. The price ratio of nitrogen to maize is thus 10.5 with these assumptions. It also assumes farmers take risk into account, rather than maximize profits, so that they use inputs only up to the point where the value of the inputs is greater than or equal to twice their costs. Using these conservative assumptions, the risk averse farmer should apply 32–37 kg/ha of nitrogen per hectare. 13 Using Benson’s response function for nitrogen on maize from 1600 on-farm trials conducted in Malawi in 1995/96, we calculate that with the optimal amount of 37 kg N per hectare, a farmer gets roughly 26 kg maize from 1 kg of nitrogen, a very high response rate, if she does not count her own labor as a variable cost (a common assumption for smallholders). With CAN costing MK 14 per kg, 1 kg of N costs MK 68.3, meaning the cost of a kilo of maize for a farmer growing her own is only MK 2.62, much less than MK 6.5, the cost if she were to buy it. For this reason, farmers realize they need chemical fertilizer, and it has become a political football in the politics of Malawi (Uttaro, personal communication). 14 An example is the fertilizer-for-work program initiated by Stephen Carr with the EU in 1991/92 when 10 000 tons fertilizer were distributed in a pilot program. Field assistants contacted local communities to ascertain what the community or village wanted done (e.g. more classrooms, wells, access roads, or teachers’ houses). In June and July when the harvest was in and there was plenty of food, and school was out, village women would provide the labor to build a teacher’s house in return for a fertilizer voucher that they could cash at planting time in November–December. 204 C.H. Gladwin et al. / Food Policy 26 (2001) 177–207

Conclusion

In this paper, we follow Sen’s thinking that food insecurity is a problem of low household incomes and poverty, and not just inadequate food production. The implications for development projects in Africa are that they cannot focus merely on increasing women’s food production. Instead, they should look for ways to improve returns to women’s resources in a broader context and facilitate women’s cash cropping, income generating activities, and agricultural labor, as well as encourage African governments to provide productivity-enhancing safety nets for the poorest women only. We recognize that African women farmers may need a long adjustment time period to diversify their income sources fully, because most African countries are at the early stages of structural transformation. During this time, rural women will employ a diversity of livelihood strategies appropriate for their environment, resources, and household composition. Some of these will be adaptive but unfortunately, some won’t. Therefore, we propose policy makers adopt a complex four- pronged strategy including different developmental interventions to address the food insecurity of women farmers. We encourage policy makers to facilitate women’s income generating activities and multiple livelihood systems, complement them with agricultural research programs aimed at increasing women’s agricultural productivity, realize that women farmers are themselves a diverse group, and provide the poorest of them with productivity-enhancing safety nets. This will be no small feat, but as Hyden (1983) states, in Africa there are “no shortcuts to progress”!

Acknowledgements

The authors are very grateful for comments received from collaborating farmers and policy planners in Malawi and E. Zambia and anonymous reviewers.

References

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