Derivation of a household-level vulnerability index for empirically testing measures of adaptive capacity and vulnerability
Abstract
Recent studies have projected significant climate change impacts in Africa. In order to understand what this means in terms of human well-being at local level, we need to understand how households can cope and adapt. This need has led many authors to argue for approaches to adaptation that are based on vulnerability analysis. Vulnerability is one of the key terms in the climate change literature, but little progress has been made in the field of its quantification. Typically, indicators are combined according to a weighing scheme, with the identification of indicators and the weighing schemes based on expert judgment rather than empirical evidence. In addition, most quantitative assessments are applied to countries or other administrative units, whereas managing climate risk has traditionally been the responsibility of households. We therefore focus on the adaptive capacity of households. We analyze the coping strategies and vulnerability to climatic stresses of agro-pastoralists in Mozambique and test the validity of a number of commonly used vulnerability indicators. We derive a household-level vulnerability index based on survey data. We find that only 9 out of 26 indicators tested exhibit a statistically significant relationship with households’ vulnerability. In total, they explain about one-third of the variation in vulnerability between households, confirming the need for more research on underlying determinants and processes of vulnerability. With inclusion of local knowledge, our study findings can be used for local targeting, priority setting and resource allocation. Complemented with studies analyzing climate change impacts and findings from country-level adaptive capacity studies, governmental policy can be informed.
Citation
Notenbaert, A.; Nganga Karanja, S.; Herrero, M.; Felisberto, M.; Moyo, S. Derivation of a household-level vulnerability index for empirically testing measures of adaptive capacity and vulnerability. Regional Environmental Change (2013) 13 (2) 459-470. [DOI: 10.1007/s10113-012-0368-4]