3.b Gender and Livelihoods_P_AP_final Sept 30 (2) (1).pdf

HOUSEHOLD ECONOMY ANALYSIS

UTILIZATION ACTIVITY

GENDER AND LIVELIHOODS

Disclaimer

The authors’ views expressed in this report do not necessarily reflect the views of the United States Agency for

International Development(USAID) or the United States Government.

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PASTORAL AND AGROPASTORAL

LIVELIHOOD ZONES

ETHIOPIA

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Acknowledgements

This report was prepared by the Household Economy Approach Utilization Activity (HEA U Activity) funded by the United States Agency for International Development (USAID). The HEA U Activity is managed by Save the Children Federation (SC) and implemented in partnership with the Government of Ethiopia National Disaster Risk Management Commission (NDRMC). In-country leadership for the HEA U Activity is provided by the Chief of Party, Waddington Chinogwenya, and Kinfe Terefe, Senior Livelihoods and Disaster Risk Management Advisor.

This report on gender and livelihoods was written by Jennifer Bush of the Food Economy Group (FEG). The HEA U Activity greatly appreciates the close collaboration with the NDRMC Early Warning and Response Directorate who led efforts to mobilize and coordinate Federal and Regional Government of Ethiopia and humanitarian partners to gather and analyze the HEA baseline information on which this report is based.

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Table of Contents

Executive Summary

Background

Objectives

Methodology

The Pastoral/Agropastoral Cluster

Female Headed Household Livelihoods

The Feminization of Poverty

The Poor Wealth Group - FHH and MHH

Assets

Sources of Food

Sources of Cash Income

Expenditure Patterns

Livelihood Impacts

The 2019 Belg Season

The 2020 Belg Season

Conclusions and Recommendations

Conclusions

Recommendations

Annex I – Data tables

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Executive Summary

The central question of this study on livelihoods and gender is whether poor female headed households are particularly disadvantaged as a household type. Or is poverty simply poverty that looks the same regardless who is head of the household?

This study answers the question in two parts. The first part is a comparative analysis of the livelihood strategies of poor female headed households (FHH) and poor male headed households (MHH) to determine whether poor FHH share similar livelihood options compared to poor MHH. Are poor FHH typically “poorer” with fewer assets compared to poor MHH? Do food and income sources vary depending on the household head and what type of work women can access? Do poor FHH rely on income options that are low value and/or that generate less income than poor MHH? This first section also examines HEA wealth group data to see if there is a “femininization of poverty”. Are female-headed households proportionately concentrated in the poor wealth groups?

The second part of the study examines the impact on food insecurity of a bad year and looks to section 1 to understand causes of any marked differences in outcomes. The objective of the analysis is to understand whether, and to what extent, poor FHH are at greater risk of food insecurity in bad years compared to poor MHH. As part of the comparative analysis, the outcome of bad years on middle households will also be used to highlight differences between and within wealth groups and thus to better see where economic status (poverty) and gender intersect.

Findings and Conclusions

1. On average across all 4 regions in the pastoral/agropastoral cluster, FHH comprise 41% and 30% of very poor and poor households, data that points to the feminization of poverty.

2. Within the poor wealth group, poor FHH form a sub-group who are that little bit poorer than poor MHH. Overall, at the cluster level, poor FHH earned on average about ETB 2,000/HH/year less than poor MHH.

3. With the same level of assets as poor MHH and with sufficient labor (i.e., older youth still living at home), poor FHH can generate a total income at the same level as poor MHH.

4. In the bad year scenario, results from the 2019 belg seasonal assessment showed that the income gap between middle and poor households, and between poor MHH and poor FHH, narrowed but poor FHH remained worse off as their starting point was that much worse. Moreover, although the income gap narrowed, the remaining income gap (roughly ETB 700-2,000) between poor MHH and poor FHH was difficult for poor FHH to close in absence of support.

5. In an average production year with mixed crop outcomes and high staple food prices, poor MHH retained a small income advantage (about ETB 1,350-2,300) over poor FHH but the income gap between the poor sub-groups did not increase.

Therefore:

1. Recognize the needs of poor FHH through gender disaggregated seasonal assessments using

LIASs set up to include FHH.

2. Acknowledge that poor FHH often find it more difficult to escape poverty and thus may be on

PSNP caseloads longer than poor MHH.

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Background

Objectives

The HEA Gender and Livelihoods study makes use of the livelihood information on poor female headed households that was collected at the village level across Ethiopia under the USAID-funded Household Economy

Approach Utilization Activity (HEA-U). The livelihood information draws from a database that covers 181 livelihood zones1. These livelihood zones can be grouped into larger livelihood clusters, including pastoral, agropastoral, mixed food crops and livestock, food crops and, lastly, a cash crop cluster. PART A of the broader study focuses on the pastoral and agropastoral cluster which includes a total of 36 livelihood zones. Of the 36 zones, 22 are included in this gender and livelihoods study as no data on poor FHH was collected in Somali Region. The remaining regions in the pastoral & agropastoral cluster include Oromia, SNNPR, and Afar (see table next page).

The objective of the study is to examine in detail the HEA data on poor FHH and poor MHH across the 22 different livelihood zones. This is new work which will complement current available HEA resources and HEA analyses, including individual livelihood profiles for each zone, regional overviews and the HEA change analyses. These documents already contain some level of description and analysis of the situation of poor FHH, but this study goes further by both providing a broader perspective at the cluster level and (conversely) focusing more exclusively on the poor, using a comparative analytical lens to assess differences between these sub-groups.

The central question of this study on livelihoods and gender is whether poor female headed households are particularly disadvantaged as a household type. Or is poverty simply poverty that looks the same regardless who is head of the household?

This study answers the question in two parts. The first part is a comparative analysis of the livelihood strategies of poor female headed households (FHH) and poor male headed households (MHH) to determine whether poor FHH share similar livelihood options compared to poor MHH. Are poor FHH typically “poorer” with fewer-and different types of assets compared to poor MHH? Do food and income sources vary depending on the household head and what type of work women can access? Do poor FHH rely on income options that are low value and/or that generate less income than poor MHH? This first section also examines HEA wealth group data to see if there is a

“femininization of poverty”. Are female-headed households proportionately concentrated in the poor wealth groups?

The second part of the study examines the impact on food insecurity of a bad year and looks to section 1 to understand causes of any marked differences in outcomes. The objective of the analysis is to understand whether, and to what extent, poor FHH are at greater risk of food insecurity in bad years compared to poor MHH. As part of the comparative analysis, the outcome of bad years on middle households will also be used to highlight differences between and within wealth groups and thus to better see where economic status (poverty) and gender intersect.

Methodology

This study relies on field work undertaken by the HEA Project to update livelihood baseline data in 181 livelihood zones across Ethiopia. HEA involves the collection of raw data at woreda, village and household level by local field teams under the technical guidance of a trained HEA team leader. Village data on production patterns and typical yields by type of crop and livestock are triangulated during interviews with household-level data that involve a detailed quantification of household assets, food and income sources, patterns of expenditure and bad year coping strategies. All data is disaggregated by wealth group and references a specific year (called the reference year).

1 The livelihood zones covered by the HEA Project are located in Oromia, Amhara, SNNPR, Sidama, Afar and Somali regions.

Benashangul Gumuz aand Gambella regions are not included in the analyses.

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HEA baseline data is integrated into a framework of analysis that measures the impact of shocks or other changes on household food and income. Two thresholds are used to measure needs: the survival threshold (below which households face hunger) and the livelihood protection threshold (below which households face livelihood erosion).

Reference material describing HEA methodology including the very detailed HEA Practitioner’s Handbook can be found on FEG’s website (http://foodeconomy.com/resources/).

No new field work was carried out for this study. Instead, the study relies exclusively on the new HEA baselines from the 2013-2016 reference years. This is possible because the new baselines included a fifth wealth group – poor FHH. The data on poor FHH provides a rich source of information for comparative analysis. The table below lists the individual baselines that form the pastoral/agropastoral cluster. Only Somali Region baselines were not included in the study as no poor FHH data was collected there.

This analysis of poor FHH livelihoods is not meant as an exhaustive study of gender and livelihoods in Ethiopia and as such a literature review was not conducted. Instead, the goal is to examine in more depth the HEA data on poor

FHH and to provide a comparative perspective at the cluster level to see if this closer look at the situation of poor

FHH brings any new understanding about gender, poverty, and livelihoods.

Region LZ code LZ name LZ #

1 Oromia ASA Abijata Shala Jido Agropastoral ORM7

2 BGP Borena-Guji Cattle Pastoralist ORM13

3 BLP Bale Agropastoral ORM14

4 BPA Bale Pastoralist ORM15

5 MCB Moyale Agropastoral, Labour and Cross-Border Trade ORM39

6 MCP Moyale Cattle, Shoats and Camel Pastoralist ORM40

7 MIP Market-Isolated Cattle and Shoat Pastoralist ORM41

8 MKP Minjar and Kereyu Pastoralist ORM42

9 NAP Northeast Agropastoral ORM44

10 OAP Southern Agropastoral ORM48

11 SNNPR ORF Omo River Flood Recession SNP29

12 SDP Surma Agro-Pastoral SNP34

13 SNA Southern Agro-Pastoral SNP37

14 SOP South Omo Pastoral SNP39

15 SPO Salamago Pastoral SNP40

16 Somali AFP Afder Pastoral SOM1

17 FDP Filtu-Dolo Pastoral SOM4

18 FKP Fik Pastoral SOM5

19 HDP Harshin Degahbur Pastoral SOM7

20 KGP Korahe Gode Pastoral SOM11

21 LHP Lowland Hawd Pastoral SOM13

22 MWP Moyale Woyamo Pastoral SOM14

23 SHP Shinile Pastoral SOM16

24 DAP Degahbur Agropastoral SOM2

25 GAP Gode Agropastoral SOM6

26 JAP Jijiga Agropastoral SOM8

27 KAP Korahe Agropastoral SOM10

28 LAP Liban Agropastoral SOM12

29 SAP Shinile Agropastoral SOM15

30 Afar AAP Asaale Agropastoral AF1

31 AGA Awsa Gewane Agropastoral AF2

32 ARP Aramis Adar Pastoral AF3

33 ASP Asaale Pastoral AF4

34 ELP Eli-Daar Pastoral AF6

35 NMP Namalefane Baadu Pastoral AF7

36 TER Teru Pastoral AF8

Sample pastoral zone for comparative data analysis

Sample agropastoral zone for comparative data analysis

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The Pastoral and Agropastoral Cluster

What are the main characteristics of the pastoral/agropastoral cluster? What are the livelihood strategies of the very poor and poor households? Do the livelihoods of poor female headed households share similar patterns as the other poor households in the pastoral/agropastoral cluster? How important is geography and wealth group as determinants of livelihood options compared to gender? This section includes a brief description of the basic characteristics of the pastoral/agropastoral cluster including: (i) location of the cluster in each region; and (ii) proportion of food from livestock vis a vis crops in the pastoral and agropastoral zones. All graphs in this section come from the Regional Overview and Change Analyses (USAID/HEA-U 2018).

The pastoral and agropastoral cluster of livelihood zones are found in most regions of Ethiopia with the exception of Amhara and Tigray Regions. The regional maps below indicate (in mustard yellow) the location of the pastoral/agropastoral cluster, specifically in the far south of SNNPR, the eastern zones of Oromia; and throughout most of Somali and Afar Regions. In total, 36 livelihood zones comprise the pastoral /agropastoral cluster of which 10 are in Oromia Region, 14 are in Somali Region, 7 are in Afar, and 5 are in SNNPR.

Livelihood Clusters – Oromia Region Livelihood Clusters – SNNPR

Livelihood Clusters – Somali Region Livelihood Clusters – Afar Region

The pastoral/agropastoral livelihood cluster is characterised by the primary importance of livestock production as both a food source and an income source. In the pie charts below, the central role of livestock in the economy is illustrated in purple showing that in Oromia and SNNPR Regions, as a weighted average, 87% of income was derived from livestock compared to 34% in the food crop cluster. Livestock production income came from milk

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(meat, skins/hides). See map below, right, illustrating household milk production. The areas with the highest production (in dark blue) are located in the far south of Oromia Region (pastoral zones).

Share of income from livestock and crops, Oromia Region Household milk production by LZ, Oromia Region

Despite the overall prominence of livestock and livestock products in the pastoral economy, the contribution of milk and livestock sales to a particular household’s economy depends on a household’s assets. Thus, the proportional importance of livestock products and sales to the household income differs by wealth group.

Wealth distribution in the pastoral/agropastoral cluster of livelihood zones is similar across most regions. In

Oromia Region, about 50% of households are in the two lower wealth groups; in SNNPR, about 45% of households fall in the two poorest wealth groups; and in Afar Region, about 55% of households are considered very poor/poor.

In general, therefore, about half of the population in the pastoral and agropastoral cluster are identified as poor.

Sources of cash income by wealth group, Oromia Region

How do livelihoods in the pastoral/agropastoral cluster vary by wealth group? As illustrated in the charts for Oromia Region at left, cash income from the sale of livestock and from milk/meat sales was the principal income source for middle and better off wealth groups. For the upper wealth groups, income was generated from camels and cattle as well as from small stock.

For the very poor and poor households, sales of goats and sheep were important, but this income was supplemented by other key income sources that included casual labor and/or self-employment. PSNP support was also a key element of livelihoods for the very poor and poor. In the pastoral/agropastoral clusters of Somali and

Afar Regions, and in eastern Oromia Region, food assistance, including PSNP, emergency food aid and school feeding, have become more important to poor households in the last 10-15 years. In the SNNPR, food transfers continued to provide an important contribution to poor households’ economy over the last 10 years, but cash transfers also increased as a mechanism for support.

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Female headed households’ livelihood strategies at the cluster level

How do livelihood patterns of poor female headed households compare to general livelihood patterns at the cluster level? Is geography the foremost determinant of livelihoods rather than gender?

Oromia Region - Poor Female headed households, Sources of Cash Income, Pastoral/Agropastoral Cluster

Poor Male headed households, Sources of Cash Income

In Oromia Region, the pattern of food and income sources for poor

FHH reflected general livelihood patterns in pastoral and agropastoral zones. In pastoral zones, poor FHH raise similar types of livestock (but slightly fewer of them) as poor MHH, and sales of goats and sheep were a common source of income for both household types although the amount earned varied by zone. Other common patterns were that milk sales were highest in pastoral areas and crop sales were highest in agropastoral zones. One difference was that poor MHH earned income from crop sales in more zones than did poor FHH. Self-employment and/or local labor comprised the principal supplementary income sources, and PSNP cash transfers were important in 5 of 10 zones for poor FHH (but only in 4-10 zones for poor MHH). Thus, poor

FHH’s livelihood strategies in Oromia Region (pastoral/agropastoral cluster) overall showed a similar pattern as poor MHH particularly the combination of livestock sales, firewood/charcoal sales and PSNP as principal sources of income.

SNNPR - Poor Female headed households, Sources of Cash Income, Pastoral/Agropastoral Cluster Poor MHH Cash Income

In SNNPR, the findings were similar to Oromia Region. Looking at the graph at left for poor FHH and the chart at right for poor MHH, the pattern of annual cash income is markedly similar for both household types. Livestock sales and PSNP cash transfers were the two key cash income sources in the reference year in pastoral areas (see for instance SOP/South Omo Pastoral). In the agropastoral zones, crop sales provided some cash income as illustrated in the Southern Agropastoral zone (SNA/SNP37). Across the cluster, livestock sales were a main source of income for both poor MHH and poor FHH. However, crop sales provided income in more livelihood zones for poor MHH compared to poor FHH. Poor MHH also earned income from honey and fish sales (pink section) which was not a common income source for poor FHH. These differences are explored in detail in the next section.

The central importance of geography and agroecology as the main determinant of livelihoods was also seen in Afar

Region. In agropastoral zones, own crops were an important food source, particularly in Awsa Gewane

Agropastoral (AGA/AF2). In pastoral zones, own milk was an important food, especially in Teru Pastoral (TER/AF8).

SOP

SNA

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The role of food transfers (yellow section) is prominent in most zones particularly in Eli Daar Pastoral (ELP/AF6).

These patterns also played out for poor MHH.

Afar Region – Poor Female Headed Households Sources of Food (2013-2015 RY) Poor Male Headed Households Food Sources

Poor FHH Sources of Cash in ETB (2013-2015 RY)

Sources of cash for poor FHH also reflected the general pattern in the cluster.

Specifically, own crops were an important income source in agropastoral zones; livestock sales, milk sales and self-employment/local labor were the cornerstones of income in the pastoral zones. In Teru Pastoral, a purely pastoral zone, livestock and milk sales were the only two sources of cash income.

This overview suggests that the principal determinant of livelihood strategies is not gender but geography and markets. Moreover, being a poor FHH does not infer a singular way of life. However, the overview already reveals some differences that suggest that in some livelihood zones, gender influences what income options are available and affects how much actual cash is earned. Some differences have already been revealed from this overview, namely that compared to poor MHH, poor FHH across the cluster earned less from livestock sales, milk sales and crop sales, and/or earned less income from honey or fish sales. These differences will be explored in more depth in the next section.

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The Feminization of Poverty

This section examines the HEA data on wealth breakdowns and in particular the prevalence of female headed households across wealth groups. HEA findings highlight the feminization of poverty, that is that female headed households are concentrated in the poorer wealth groups. This finding alone suggests that gender is a factor in shaping the economic constraints and opportunities faced by female headed households and limit their exit from poverty. As a group, they face greater risks of food insecurity and income stress.

Percentage of Female Headed Households by Wealth Group and by Region

Oromia Region SNNPR Afar Region

HEA baselines begin with a description of each wealth group, using local perspectives to derive an estimate of the wealth breakdown and the proportion of female head households in each wealth group. The data from village key informants in 3 regions –SNNPR, Afar and Oromia – is detailed in the table left.

Female headed households are found in all four of wealth groups so clearly not all female headed households are poor. A mature widow with adult sons living at home and with land, oxen and other livestock assets has as much potential to secure a good livelihood as other middle or better off households. However, there is a marked concentration of female headed households in the lower wealth groups and it is this trend that calls for a more detailed look at female headed households as sub-group of the poor. Overall, very poor and poor female headed households comprised roughly 16% of all households across the 3 regions. By contrast, middle and better off female headed households are just 8% of all households. But as a sub-group, female headed households comprised 39% and 28% of the very poor and poor wealth groups respectively. Amongst the better off, female headed households were about 10% of the wealth group.

The HEA wealth group data shows conclusively that female headed households are clustered in the bottom wealth groups. The HEA data itself does not explain the causes for this feminization of poverty. Do the stresses of poverty result in more divorces or to more men’s early deaths or to husbands migrating away and not returning?

Or once they become widows or single mothers are women more likely to slide into poverty and remain there?

This study does not answer these questions, important as they are. Nonetheless, the trend is clear and with the feminization of poverty underscored as a key issue, it is important to turn attention to the poor wealth group itself and examine gender differences in livelihood options.

% of HH who are female-headed

Region Wealth Group MHH FHH Total

SNNPR VP 12% 6% 18%

P 19% 8% 27%

M 31% 7% 38%

BO 15% 2% 17%

total 77% 23% 100%

Afar VP 12% 13% 25%

P 21% 9% 30%

M 25% 5% 30%

BO 14% 1% 15%

total 72% 28% 100%

Oromia VP 13% 6% 19%

P 21% 7% 28%

M 30% 6% 36%

BO 15% 2% 17%

total 79% 21% 100%

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The Poor Wealth Group - FHH and MHH

Within the poor wealth group, how does the situation of poor female headed households compare to poor male headed households? Are most poor households constrained by the same obstacles (such as limited assets and resources, and limited education/skills) or are certain obstacles gender-specific? This section looks at the poor – disaggregated by FHH and MHH – and at to what extent food and income patterns in the pastoral/agropastoral cluster are affected by gender.

Poor female headed households are not a single, uniform/homogenous group. Across the country, their livelihoods differ depending on geography and market access, just as for male headed households. Bearing this in mind, what aspects of livelihood strategies are related to gender and what implications does this have for coping and long-term resilience? The objective of this section is to analyse whether poor FHH share similar livelihood options compared to poor MHH. Are poor FHH typically “poorer” with fewer assets compared to poor MHH? Do food and income sources vary depending on the household head and what type of work women can access? Do poor FHH rely on income options that are low value and/or that generate less income than poor MHH?

Assets

For the most part, across the pastoral/agropastoral cluster, poor FHH have roughly one person less in their household than poor MHH. The average household size for the pastoral cluster is 6.3 and 5.5 people/household for poor MHH and poor FHH respectively and is roughly the same for the agropastoral cluster (see tables below). On the one hand, this means that poor FHH need less income to cover the basic needs of their smaller household. On the other hand, it means that poor FHH typically have a higher dependency ratio (more children to adults) which has implications for their livelihood from labor availability (and thus earning potential) to types of work that they can access and/or fit into their other domestic responsibilities.

Poor FHH also typically own fewer assets than poor MHH. Key assets in the pastoral and agropastoral cluster include land, labor, and livestock. Poor FHH own and cultivate less land across the cluster. Farming is marginal and opportunistic especially in pastoral zones and poor FHH cultivate a smaller proportion of their land than poor MHH due to less labor availability as well as, perhaps, other factors such as fewer oxen and other inputs.

Pastoral Cluster Land Assets by Household type Agropastoral Cluster Land Assets by Household type

Agropastoral Oromia SNNPR Afar

POOR HH MHH FHH MHH FHH MHH FHH Ave MHH Ave FHH

HH size 7.1 5.9 6.0 5.7 6.8 5.8 6.6 5.8

Pastoral Oromia SNNPR Afar

POOR HH MHH FHH MHH FHH MHH FHH Ave MHH Ave FHH

HH size 6.7 5.8 5 5 7.1 5.8 6.3 5.5

0.0

0.1

0.2

0.3

0.4

Land area owned Land cultivated

Land assets in ha - Pastoral Cluster - Poor HH

Ave MHH Ave FHH

0.0

0.2

0.4

0.6

0.8

1.0

Land owned (ha) Land cultivated Food crops (ha) Cash crops (ha)

Land assets (ha) - Agropastoral Cluster - Poor HH

Ave MHH Ave FHH

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In the agropastoral zones, most of the land owned by poor FHH is cultivated but poor FHH own and cultivate less land than poor MHH. Poor households in general focus on food crops namely, maize, sorghum and haricot beans

Other crops -- wheat, teff, millet, potatoes, sweet potatoes and vegetables -- are also grown in specific zones.

Pastoral Cluster Livestock Assets by Household type Agropastoral Cluster Livestock Assets by Household type

Livestock assets also show a clear pattern by gender. For all the main types of livestock, poor FHH own fewer animals than poor MHH. The differences are more apparent in the agropastoral cluster where on average poor

FHH own 2 fewer goats and 1 less cow than poor MHH. In pastoral zones, poor FHH on average own 1 less sheep,

0.5 fewer goats and 0.5 fewer cattle. Smaller herds point to the challenges faced by women to acquire animals through herd growth, gifts and/or purchase. Poor FHH also face labor and financial obstacles when managing the herd, including paying for inputs such as vaccinations and medications, fodder, salt and so on. With fewer assets than poor MHH, poor FHH consequently have a more fragile livelihood.

Education is also considered an asset to the extent that it offers children additional skills to adapt to a changing environment and is therefore an investment in the future. About the same number of children from poor FHH finish Form 4 as from poor MHH although in both the pastoral and agropastoral clusters, the numbers are very slightly lower for poor FHH, indicating, perhaps, some income constraints limiting school attendance as well as labor demands on children to engage in economic activities. The other noted result is that on average, in poor households, fewer girls finish Form 4 than boys especially in pastoral zones. Lower levels of education amongst girls repeats cycles of disadvantage affecting livelihood options if and when these girls become head of their own household.

Pastoral

POOR HH Ave MHH Ave FHH

Boys in school (Form 4) 2.0 1.8

Girls in school (Form 4) 1.3 1.3

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

Goats Sheep Cattle Donkeys Camels beehives Ox

Livestock assets - Pastoral CLuster - Poor HH

Ave MHH Ave FHH

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

Goats Sheep Cattle Donkey Ox Camels beehives hens

Livestock assets - Agropastoral Cluster - Poor HH

Ave MHH Ave FHH

Agropastoral

POOR HH Ave MHH Ave FHH

Boys in school (Form 4) 1.3 1.2

Girls in school (Form 4) 1.0 1.0

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Sources of Food

Pastoral Cluster – Poor FHH and Poor MHH Agropastoral Cluster – Poor FHH and Poor MHH

In the pastoral and agropastoral clusters, there is very little difference in the percentage of annual food energy secured by poor MHH and poor FHH. The results are illustrated in the graphs above which compare annual food energy across a sample of 5 pastoral and 6 agropastoral livelihood zones in Oromia, SNNPR and Afar Regions. Most of the poor, both MHH and FHH, secured about 100% of their food needs, with a range of 96% to 104% in the pastoral cluster (Borena-Guji Pastoral/ORM13 and Teru Pastoral/AF8 respectively), and a range of 97% to 115% in the agropastoral cluster (Omo River Flood Recession/SNP29 and Awsa Gewane Agropastoral/AF2 respectively).

Food Sources by poor FHH and poor MHH in 3 Pastoral zones Food Sources by poor FHH and poor MHH in 4 Agropastoral zones

The picture is more complex when looking at the contribution of specific food sources to annual food energy at the level of the livelihood zone. For instance, in Borena-Guji Cattle Pastoral (BGP/ORM13), there are gender differences in own crop consumption. Specifically, poor MHH produce and consume more own crops compared to poor FHH because they own and cultivate more land (0.5ha compared to 0.25ha). This pattern is repeated in the agropastoral cluster. In most cases (but not all), this is attributed to more labor and more land owned and cultivated by poor MHH compared to poor FHH.2 The implication is that poor FHH must access more food from other sources. It most cases, in this cluster, this means either eating a little less or else buying more food by shifting more of their annual income into food purchases. This has two effects. It means poor FHH have less income for other essential expenses. It also means that they are more vulnerable to rises in staple food prices than poor MHH. In the pastoral cluster, food transfers have helped to bridge the gap and provide a buffer against high staple food prices.

2 The exception to the cluster trend is South Omo Pastoral (SOP/SNP39) where the contribution of own crops is the same for both poor FHH and poor MHH and where the household size and land holdings is the same across the poor wealth group.

0%

20%

40%

60%

80%

100%

120%

BGP BPA SOP ARP TER

ORM13 ORM15 SNP39 AF3 AF8

Food sources (% of annual kcal) - Poor HH

Male HH Female HH

0%

20%

40%

60%

80%

100%

120%

MHH FHH MHH FHH MHH FHH

ORM 13 SNP39 AF3

Food sources Pastoral - Poor HH crops livestock products payment in kind purchase food aid other (gifts, wild food, fish etc)

0%

20%

40%

60%

80%

100%

120%

MHH FHH MHH FHH MHH FHH

ORM48 SNP37 AF2

Food Sources Agropasatoral - Poor HH crops livestock products purchase food aid other (gifts, wild food, fish etc)

0%

20%

40%

60%

80%

100%

120%

NAP OAP ORF SNA AAP AGA

ORM44 ORM48 SNP29 SNP37 AF1 AF2

Food sources (% annual kcal) - Poor HH

Male HH Female HH

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Own milk consumption shows a more mixed picture. Poor FHH typically own fewer cattle and goats but with fewer mouths to feed, milk contributes to about the same proportion of annual food needs for both poor FHH and poor

MHH in the pastoral cluster. In the agropastoral cluster, poor FHH typically consumed less own milk although differences overall for the cluster were small (6% of annual food needs from own milk consumption for poor MHH compared to 4% for poor FHH).

In sum –

In the pastoral cluster, poor FHH overall secured slightly less annual food energy than poor MHH from own crop and milk production (22% to 26% respectively)

In the agropastoral cluster, poor FHH overall produced and consumed fewer own crops and own milk than poor

MHH (45% and 51% of annual food needs respectively)

Sources of Cash Income

Pastoral Cluster Agropastoral Cluster

Across the pastoral and agropastoral cluster, poor FHH typically earned less cash income than poor MHH. This pattern is clearly shown in the graphs above comparing the annual cash income of poor MHH and poor FHH by sample livelihood zone. Results for total (food+cash) income also showed the same pattern: in the reference year, poor FHH typically earned less income and secured less food than poor MHH across the cluster.3 In the total income calculation, the differences between poor MHH and poor FHH were smaller than in the cash income results. Nonetheless, the pattern holds true.4

3 In HEA, total income is a measure of the total food secured and the total cash income earned as measured by how much of the staple food basket that income meets. Total income is calculated by livelihood zone and all wealth group income is adjusted to the household size of the poor, and thus can be used as a proxy for per capita earnings.

4 An exception was Teru Pastoral where poor FHH’s total income was greater than poor MHH (see total income graph, pastoral zones). By contrast, in Borena-Guji Pastoral, poor MHHs’ total income was ETB 2,000 higher than poor FHH. In the agropastoral cluster, the greatest income difference was in Southern Agropastoral (SNA/SNP37) where the total income of poor MHH was ETB 2,615 higher than poor FHH.

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BGP BPA SOP ARP TER

ORM13 ORM15 SNP39 AF3 AF8

Annual cash income Pastoral - Poor HH

Male HH Female HH

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ORM44 ORM48 SNP29 SNP37 AF1 AF2

Annual cash income Agropastoral - Poor HH

Male HH Female HH

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Pastoral Cluster – Total (Food+Cash) Income Agropastoral Cluster – Total (Food+Cash) Income

Are there particular activities that produce these gender differences in annual income? Data from Bale Pastoral

(BPA/ORM15) and Borena-Guji Agropastoral (BGP/ORM13) provide examples of different income patterns between poor FHH and poor MHH. In Bale Pastoral, for instance, poor MHH earned more cash from livestock sales than poor FHH.5 Poor MHH do not have significantly larger herds than poor FHH but owning an additional cow and

2-3 more shoats allowed them to sell, for instance, one additional sheep, 0.5 goats and 0.5 cattle leading to ETB

2,750 more in livestock sale income alone. In Borena-Guji Agropastoral, cash income differences were not large, but poor MHH earned more cash from milk sales and casual labor compared to poor FHH leading to an overall difference of ETB 1,100. Labor income came from one adult earning cash from 1-2 months of casual labor, including salt and gold mining (migratory labor), local agricultural labor, firewood and charcoal sales. Although not typical, some poor FHH earned a little cash from petty trade, firewood and charcoal sales. Generally, poor FHH did not earn any cash from mining and migratory labor.

Pastoral Cluster – Annual Cash Income BPA Agropastoral Cluster – Annual Cash Income BGP

In the pastoral zones, livestock are a key asset even for the poor. The examples above show that in certain zones, poor MHH earn more income from livestock and/or milk sales compared to poor FHH. Can the results from these two zones be generalised across the cluster? Do poor FHH typically earn less income from milk and livestock sales compared to poor MHH?

5 Poor MHH have more livestock – 3 cattle to poor FHHs’ 2 cows; 5 goats to poor FHH’s 3 goats; and 1.5 sheep to poor FHH’s 0 – which allows them to generate more sales and hence more cash.

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Annual cash income in ETB - Poor HH

ORM13/BGP

crop sales livestock product sales livestock sales labour/employment

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Male HH Female HH

Annual cash income in ETB - Poor HH

ORM15/BPA

PSNP

self-employment + petty trade livestock sales livestock product sales

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Total income Pastoral Cluster - Poor HH

Male HH Female HH

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Total income in ETB Agropastoral - Poor HH

MHH FHH

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Pastoral Cluster – Annual milk production by zone Pastoral Cluster – Cash income from milk sales by zone

In three of the sample pastoral zones, there is little to no difference in milk production (litres/year) between poor

FHH and poor MHH. However, in two zones – Bale Pastoral and Aramis Adar Pastoral – total milk production was higher for poor MHH as they owned more milk cows compared to poor FHH. The data on milk sales across the sample pastoral zones is similarly mixed. In two zones, poor FHH earned slightly more income from milk sales than poor MHH. In the other two zones, the situation was reversed and poor MHH sold more milk than poor FHH. The reasons why milk sales between poor FHH and poor MHH differed in each zone were not very clear.

At the level of the livelihood zone, therefore, data does not reveal clear gender patterns in milk production and income from milk sales. However, at the level of the cluster, poor MHH earned ETB 105 more income from milk sales than poor FHH. This difference is relatively small.

Pastoral Cluster – Cash income from livestock sales by zone

Livestock sale income also shows a mixed picture at the level of the livelihood zone. For instance, in three of the sample pastoral zones, poor MHH earned more cash from livestock sales than poor FHH but there was little or no income difference in the other two zones. Overall, at the cluster level, poor MHH earned about ETB 750 more than poor FHH in the reference year from livestock sales. This difference is also reflected in livestock assets. For all 3 main types of livestock (cattle, goats, and sheep), poor

FHH’s stock holdings were lower than poor MHH at the cluster level (see table below).

Pastoral Cluster – livestock assets by region and cluster

BGP BPA SOP ARP TER

ORM13 ORM15 SNP39 AF3 AF8

Milk production (litres/year) - Poor HH

Male HH Female HH

BGP BPA SOP ARP TER

ORM13 ORM15 SNP39 AF3 AF8

Income from milk sales in ETB - Poor HH

Male HH Female HH

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Income from livestock sales in ETB - Poor HH

Male HH Female HH

Pastoral Oromia SNNPR Afar

POOR HH MHH FHH MHH FHH MHH FHH Ave MHH Ave FHH

Camel number owned 0 0 0 0 1.8 1.0 0.6 0.3

Cattle number owned 4.8 4.4 7.5 7.5 2.2 1.5 2.4 2.0

Ox number owned 0.3 0.2 0.5 0.25 0.0 0.0 0.3 0.2

Goat (or shoat) number owned 7.5 6.2 8.5 8.5 13.0 13.2 9.7 9.3

Sheep number owned 4.3 2.4 3.5 3 8.3 8.2 5.4 4.5

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Pastoral Cluster – Annual Cash Income by Region – Poor HH

Overall, in the reference year, poor

MHH earned ETB 2,120 more cash income than poor FHH at the level of the pastoral cluster (excluding

PSNP transfers).

Agropastoral Cluster Annual Cash Income by Region – Poor HH

In the agropastoral cluster overall, poor MHH earned ETB 2,041 more than poor FHH in the reference year. The income sources with the greatest differences were livestock sales (ETB 780) and crop sales (ETB

782). These are the two chief sources of income in the agropastoral zones, so it is perhaps not surprising that the greatest income differences were noted for these two sources.

Agropastoral Cluster - Annual Cash Income, Average by Region – Poor HH

Annual Cash Income table excludes PSNP transfers

Other differences were smaller in cash terms (i.e., ETB 100 for milk sales). For self-employment, poor FHH earned about ETB 500 more than poor MHH, but poor MHH earned ETB 620 more than poor FHH from local/migratory labor.

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Oromia SNNPR Afar

Pastoral Annual Cash Income in ETB - Poor HH

Crop sales Milk sales

Livestock sales self employment local labour other (honey, fish sales, remittances)

Pastoral

POOR HH Ave MHH Ave FHH

Crop sales 142 0

Milk sales 490 385

Livestock sales 4952 4204 self employment 2452 1755 local labour 372 391 honey, fish sales, remittances 744 367

Total (average) 9152 7103

Agropastoral Oromia SNNPR Afar

POOR HH MHH FHH MHH FHH MHH FHH Ave MHH Ave FHH crop sales 1666 1215 1532 1545 3510 1603 2236 1454 livestock product sales 961 1030 1553 1310 75 0 863 780 livestock sales 3883 2932 7794 7562 4580 3423 5419 4639 labour/employment 2662 1056 0 107 810 450 1157 538 self-employment + petty trade 2103 2283 930 557 1920 3615 1651 2152 other (gifts, remittances) 60 0 518 0 1750 1500 776 500

Total (average) 11335 8516 12327 11080 12645 10590 12102 10062

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Oromia SNNPR Afar

Agropastoral HH annual cash income in ETB - Poor HH crop sales livestock product sales livestock sales labour/employment self-employment + petty trade other (gifts, remittances)

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Gender differences in income sources were less clear at the level of the livelihood zone particularly for supplementary income sources (such as local labor and self-employment). Opportunities specific to a zone at times benefited men compared to women (such as local mining or gold panning) but in other zones, some types of self employment benefited women (such as handicrafts). For this reason, it is hard to generalise about labor and self-employment patterns across the cluster and across all 4 regions except to say that as a rule of thumb, poor FHH with a high number of dependents typically sought work that was not far from home and that fit in with her other daily productive and domestic activities.

In sum –

For the pastoral cluster overall, poor MHH earned more cash from key income sources (namely milk sales and from livestock sales) than poor FHH, but the picture is complex when data is analysed by individual zone.

For the agropastoral cluster overall, poor MHH earned more than poor FHH from crop sales, milk sales, livestock sales and labor. At the cluster level, poor FHH earned more than poor MHH from self-employment.

Expenditure Patterns

As poor MHH typically earn more cash income, does this result in gender differences in spending that may lead to better productive outcomes (spending on inputs for example) or more investment in health, hygiene and/or education?

Overall, at the cluster level for pastoral zones, the results reflect that higher earning by poor MHH resulted in more spending on basic needs including food, household items, livelihood inputs, education, health and clothing. On a per capita basis, these differences become smaller or disappear. For instance, across the pastoral zones overall, poor MHH met 47% of their annual food need through purchase and poor FHH met 46%. There were also exceptions in some livelihood zones, such as in Borena-Guji Pastoral, where poor FHH spent more on food than poor MHH (but produced fewer crops for own consumption than poor MHH).

Pastoral Cluster Annual Expenditures Poor HH

For poor households, livelihood inputs are not typically a large expenditure item due to their few assets and low income. In general, poor MHH do spend more than poor FHH on livelihood inputs across livelihood zones in the pastoral cluster, including on items such as animal drugs, fodder, livestock purchase and seeds.

Pastoral

POOR HH Ave MHH Ave FHH staple food 3207 2722 non-staple food 1444 1413

HH items 1428 1165 water 12 3 livelihood inputs 426 212 education 348 286 health 442 331 clothing 765 664 phone/transport 205 88 other 830 481

Total (average) 9106 7364

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Pastoral HH annual expenditure in ETB - Poor HH staple food non-staple food HH items water livelihood inputs education health clothing phone/transport other

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However, as seen in the graph at left, the overall average was significantly affected by results in

South Omo Pastoral where poor MHH invested in purchasing a goat in the reference year. Excluding

South Omo Pastoral, differences in livelihood input spending were small (roughly ETB 190/HH/year).

Another category that poor MHH spent more than poor FHH across the cluster’s livelihood zones is on the “other” category. Principally, this is due to more spending on qaat/tobacco/cigarettes/alcohol as well as more spending on gifts/festivals. This type of discretionary spending does not provide future benefits but it does reflect that poor FHH operate on a very lean budget with very little money for discretionary expenditures.

Agropastoral Cluster Annual Expenditures Poor HH

In the agropastoral cluster, patterns of average annual expenditures show that on balance poor MHH spent more than poor FHH across all spending categories, but the margins are generally small especially on a per capita basis.

Poor MHH spent more than poor FHH on food, but food purchases met more of the annual food needs of poor

FHH (38%) compared poor MHH (36%) because poor FHH on average have smaller households.6 Differences in spending on livelihood inputs was around ETB 200, mainly due to higher spending on animal drugs by poor MHH.

In Oromia agropastoral zones, poor MHH also spent around ETB 115 more per year on fertiliser compared to poor

FHH. The “other” category also shows a greater difference in expenditures between poor MHH and poor FHH. This reflects higher spending by poor MHH on gifts/religious contributions/festivals, house repair, and, in Afar, on qaat.

In sum –

Across the pastoral and agropastoral cluster, there was little difference in spending on basic needs between poor MHH and poor FHH households especially on a per capita basis. Poor MHH did spend a little more on livelihood inputs which could provide some future advantages. Poor MHH also spent more on the “other” category, including on qaat.

6 Conversely, poor MHH met more of their annual food needs from own crop consumption (46%) compared to poor FHH (43%) due to larger land holdings on average and more investment in livelihood inputs.

BGP BPA SOP ARP TER

ORM13 ORM15 SNP39 AF3 AF8

Spending on livelihood inputs in ETB - POOR HH

Male HH Female HH

Agropastoral

POOR HH Ave MHH Ave FHH staple food 2200 2154 non-staple food 2173 2119

HH items 2013 1833 water 92 81 livelihood inputs 1353 1179 education 549 511 health 719 497 clothing 1142 923 phone/transport 353 215 loan repayment 0 0 other 1407 680

Total (average) 12002 101900

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Agropastoral HH annual expenditure in ETB - Poor HH staple food non-staple food HH items water livelihood inputs education health clothing phone/transport loan repayment other

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Livelihood Impacts – the 2019 Belg Season

What is the impact of a bad season on the poor wealth group? Do poor FHH fare comparatively better or worse than poor MHH when hit with poor crop yields, declining herd sizes, reduced milk yields, and poor terms of trade? What do the income differences mean in context of local incomes? The 2019 belg season outcome analysis includes a comparison of poor and middle households to put into perspective the magnitude of impacts both between and within wealth groups.

The belg 2019 season marked a particularly difficult time for pastoralists in much of Ethiopia. In the Borena-Guji cattle zone (BGP/ORM13) in southern Ethiopia, herd sizes for camels, cattle and shoats declined to about 50-70% of the reference year size, and excess mortalities in the belg 2019 season were an estimated 5-10%. This led to significant loss of income from milk sales and livestock sales. Crop production was also very poor. Maize yields were less than 30% of the reference year and haricot bean outcomes were likewise very poor. Consequently, food and income from crop production declined by about two-thirds compared to the reference year.

How did the very poor belg 2019 season affect poor FHH compared to poor MHH? The results for the season are illustrated in the three graphs below which compare the results by wealth group. There are two important findings to note. First, the initial deficit shows that poor MHH lost more income than poor FHH (ETB 8,800 for poor MHH compared to ETB 6,300 for poor FHH).7 In terms of loss of income, the impact of drought and livestock mortality in the belg 2019 hit poor MHH harder than poor FHH because households with productive assets had more to lose.

Poor FHH were less exposed to this type of shock (i.e., drought) because they had fewer livestock and less land and crops to be lost. The impact of the very poor belg 2019 narrowed the income gap between the two poor sub-groups from a difference in income of ETB 3,000 in the reference year to a difference of ETB 690 in a bad year.

2019 Belg Seasonal Assessment by Wealth Group, Borena-Guji Cattle Pastoral

Poor FHH Poor Middle

However, to point 2: although the severity of income loss was higher for poor MHH, poor FHH were still worse off than poor MHH in a bad year. In short, poor MHH still earned ETB 690 more than poor FHH. Small differences in income sources – a little cash from migratory labor and milk sales – led to these small differences in total income.

7 The initial deficit refers to the deficit calculated without external food and cash transfers and before coping strategies are considered.

District: Liben_P

Livelihood Zone: BGP/ORM13

Household type: PFHH

Total Income (food+cash)

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14,000 ref.year curr.year thresholdsc a s h i n c o m e p e r h o u s e h o ld p e r y e a r l/hoods protection survival

Thresholds psnp/food aid wild foods/other gifts/remittances migrant labour livestock sales crop sales crops milk/butter sales milk

District: Liben_P

Livelihood Zone: BGP/ORM13

Household type: P

Total Income (food+cash)

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14,000 ref.year curr.year thresholdsc a s h i n c o m e p e r h o u s e h o ld p e r y e a r l/hoods protection survival

Thresholds psnp/food aid wild foods/other gifts/remittances migrant labour livestock sales crop sales crops milk/butter sales milk

District: Liben_P

Livelihood Zone: BGP/ORM13

Household type: M

Total Income (food+cash)

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35,000 ref.year curr.year thresholdsc a s h i n c o m e p e r h o u s e h o ld p e r y e a r l/hoods protection survival

Thresholds psnp/food aid wild foods/other gifts/remittances migrant labour livestock sales crop sales crops…