The Rural Water Livelihoods Index - FAO

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The Rural Water Livelihoods Index
choice. It is important to note that if comparisons are to be made between scores for different locations or situations, the
weightings used must be the same in all cases.
Weights are effectively multiplicative factors which are applied to each component. When totalled, weights must equal 100
(%). A weight of 30% means that the specific domain score for that particular component is multiplied by 0.3.
Five approaches to allocation of weights are discussed below:
• entirely arbitrary
• determined by consensus
• determined by policy relevance
• empirically driven
• driven by theoretical considerations
Arbitrary Weights
When weights are chosen without reference to theory or empirical evidence, or even when equal weights are selected, this
is classed as ‘arbitrary’.
Weights determined by consensus
In this case, policy makers and stakeholders could simply be asked for their views and the choices obtained by consensus.
Weights determined by policy relevance
Components can be weighted in accordance with public expenditure on particular areas of policy.
Weights driven by theoretical considerations
In the theoretical approach, account is taken of the available research evidence which informs the theoretical model of
what is being examined, and weights are assigned according to this. (e.g., if deriving an index of susceptibility to Malaria,
the theory suggests that the presence of specific mosquito types is essential to the transmission of Malaria. This would
imply that this would have the greatest weight, while other issues, such as presence of standing water, would be less
important, and so would have less weight).
Empirical approaches to weighting
There are two sorts of approaches that might be applicable here. First, analysis of an existing survey might generate
weights. Here one might construct a proxy for the issue being examined, and multivariate predictive modeling can be used
to derive weights. Second, factor analysis (Senior, 2002) to extract a latent ‘factor’ representing the issue can be used,
assuming that the analysis permitted a single factor solution.
Weighting scheme used for RWLI
In this scoping study, we have examined how others involved in index development have dealt with this (Murphy, 1999;
Noble et al., 2000) and have decided, that for our purposes, the most effective approach is to allocate weightings in such
a way as to ensure that each of the four major components are equally weighted, while at the same time, each of the subcomponents
is given an equal weight within that component. It is important to note that if the number of sub-components
changes, for example if data is missing, this alters the implicit weight of the other sub-components. For this reason, in this
exercise, all missing data were replaced by estimates or proxies, and countries with too much missing data were excluded.
Excluded countries are shown in Appendix V. Hence, an equal weighting schemes was used in which each component
accounts for up to _ of the total RWLI value (and each subcomponent up to 1/8 of the value).