Planning to reduce the impact of global climate change on the populations of developing countries requires a method of assessing human vulnerability. Household economy methods can be used in this context to better understand the nature of vulnerability and to consider ways to limit its effects – for example, the methods can help researchers and policy makers to monitor the impacts on livelihood systems of multiple stress factors (such as increased frequency of flooding, changes in seasonal rainfall patterns or reduced agricultural production), to identify the people that are least able to adapt to change, and to assess the levels of assistance required.
Some of the impacts of climate change can be reduced by flood control and other measures to strengthen infrastructure, developing drought-resistant crops, and providing social protection to help households to overcome falls in income and maintain their resilience. However, identification of the specific vulnerabilities (linked not only to specific at-risk livelihood activities and locations but also to the wider social, political, economic and technological context) of different households and groups may also be needed. Household economy methods can assist with this, by providing reliable data on households’ livelihoods and other characteristics that contribute to defined vulnerabilities, and generating transparent and convincing output that can drive action.
Many southern and eastern African governments now routinely use the household economy approach (HEA) for regular, practical and effective vulnerability assessments. The HEA is a significant source of data on rural livelihoods: the simplified large-area data has some limitations, but HEA data from many African countries currently forms the only available dataset describing livelihoods for wide areas of the continent (for it to be sustained, further capacity building, improved systems of data management and wider engagement are needed). This data opens up many possibilities:
The individual household method (IHM®) allows for further disaggregation of household data and can be used for designing, monitoring and measuring the impacts of development programmes at a household level. This more nuanced and comprehensive data can be used in both urban and rural contexts:
Dr Lucy Wallace EfD Communications Manager | CSAT Programme Manager Research inevitably means we spend an awful lot of time working in one small area. The mystical ‘bigger picture’ is relatively distant, it’s something we refer to in grant applications, and we often don’t know where to start to attain the coveted ‘research into policy […]
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