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Moving Up or Moving Out? Explaining the Livelihood Trends in Pastoralist Areas Andy Catley.

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Presentation on theme: "Moving Up or Moving Out? Explaining the Livelihood Trends in Pastoralist Areas Andy Catley."— Presentation transcript:

1 Moving Up or Moving Out? Explaining the Livelihood Trends in Pastoralist Areas Andy Catley

2 Two policy narratives “Vulnerability and destitution are increasing in pastoralist areas due to conflict, climate change and weak governance”. “Economic growth and development should be driven by trade. Pastoralists need to be more integrated into export markets to reduce poverty”.

3 Trends in livestock ownership by wealth group over 60 years ( ), Shinile zone, Somali Region, Ethiopia (Source: adapted from Kassahun et al., 2008)

4 Other data Proportional wealth group data from Somali Region ‘livelihoods baselines’ indicates, over 8 years: – 5% increase in proportion of ‘poor’ households – 5% decrease in proportion of ‘middle wealth’ households – No change in proportion of ‘better off’ households But, apply a 2.5% annual population growth to this data and absolute trends can be estimated: – 4.1% annual increase in number of poor households – 0.8% annual increase in number of middle-wealth households – 2.5% annual increase in number of wealthy households

5 Commercialization impacts In Somali and Borana areas of Ethiopia, a gradual redistribution of livestock assets from poorer to wealthier herders A growing asset gap between rich and poor – More difficult for the poor to ‘move up’ to a more viable middle- wealth status – More difficult for poor to rebuild herds after drought Appropriation of key natural resources by wealthier actors – Water and private birkeds, Somali Region – Private land distribution, Somali Region – Private rangeland enclosures, kallos, in Borana

6 Commercialization, ‘Moving Up and Moving Out’ Wealthy Livestock holdings/person Number of people + Medium wealth Livestock holdings/person +++ Number of people ++ Poor Livestock holdings/person + Number of people ++++ Destitute Livestock holdings/person - Number of people +++ Capacity to respond to increasing market demand for livestock Purchasing power Capacity to access, control or sell decreasing grazing and water resources Capacity to withstand drought and rebuild herds Commercialization Moving Up Positive feedback loops – increasing assets, increasing influence and capacities Moving Out Negative feedback loops – decreasing assets, decreasing influence and capacities Long-term ‘constants’ Rainfall variability and drought Conflict

7 History Agricultural development globally characterized by absorption of small units by large units during commercialization Commercialization and pastoralism (Middle East etc.) – Growth of industries (oil) and urban centers, with growing demand for meat and milk – Pastoral commercialization – Social and economic isolation of poorer households – Outmigration for the poor, who are forced out – Pastoralism survives, but in a more commercialized form, with relative fewer but larger herds

8 Policy implications Understand the long term trends; support area-wide economic analysis e.g. spaces for ‘diversification’ and ‘alternative’ livelihoods within pastoralist areas Commercialization is inevitable, and driven by demands outside of the region Examine the objective rainfall data and long-term trends – distinguish ‘drought’ as defined by rainfall vs. drought as defined by livelihoods impacts Safety nets and ‘asset building’ – Limited impact expected wrt long-term viable livelihoods in pastoral areas Alternatives – Accelerate education – Policy support to outmigration Not novel ideas

9 Acknowledgements Initial regional analysis funded by the IGAD-FAO Livestock Policy Initiative. Livelihoods-conflict analysis in Shinile zone, Ethiopia, funded by the Foreign and Commonwealth Office, UK, via a grant to Mercy Corps. Ethiopia analysis funded by Ukaid from the Department for International Development. Rainfall analysis funded by USAID Ethiopia under the Pastoralist Livelihoods Initiative (PLI) Policy project. Thanks to Francis Chabari for sourcing the Kenya rainfall data.


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