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:
Some of you may have seen this piece on the BBC about “How missing weather data is a ‘life and death’ issue”. It’s about tech start-up Kukua, and the weather stations they have installed in Tanzania to help provide local commercial farmers with better forecasts. Kukua is a business with a rather unusual business model: […]
In September, I was able to attend the AMCOMET, African Ministerial Conference on Meteorology, forum in Addis Ababa. The focus of the forum was Weather, Water, and Climate Services, and the contribution of these ‘hydromet’ services to wider social and economic development is becoming increasingly evident as the reality of climate change hits both urban […]
Just over a year ago the UK Department for International Development (DfID), with the Natural Environment Research Council (NERC) launched its ‘Future Climate for Africa’ (FCFA) project. This £20 million project, involving five research consortia, aims to “generate fundamentally new climate science focused on Africa, and to ensure that this science has an impact on […]