Third, the joint distribution between consumption and health outcomes is often missing because monetary and non-monetary outcomes are typically collected through separate surveys. The classical solution used by global multidimensional poverty measures is to ignore the data on one of these two key aspects of well-being. We identify three alternative methods to construct a hybrid index accounting for data coming from separate surveys. The first two methods consist in assuming a value for the missing joint distribution, while the last method assumes equal non-monetary outcomes at the local level. The first method assumes the overlap between the monetary and the non-monetary poverty head-count ratios. We show in one context that this method yields better wellbeing comparisons than the classical solution regardless of the exact value assumed for the (unobserved) overlap. Shockingly, “making up” overlap data can improve well-being comparisons. The reason is that it allows increasing the amount of data used. The second method consists in imputing consumption into the non-monetary survey. We argue that the relevant benchmark to evaluate the relevance of such imputation approach is not whether the joint distribution assumed is sufficiently correct but rather whether it improves well-being comparisons. The third method consists in constructing a “total consumption” variable that aggregates monetary consumption with monetary valuations of non-monetary outcomes, which are considered equally distributed at local level. We propose one way of constructing the “total consumption” variable that recognizes that each core dimension of well-being is essential.

The second source of potential improvements relates to better filtering the data used. We identify two ways in which this could be done. The first is to move beyond the default procedure that assigns equal weights to all dimensions. This procedure has the advantage of being applicable without information on the relevant preference, but runs the risk of making implausible trade-offs. Some information on the relevant preference can be obtained from subjective well-being data or from dedicated preference elicitation surveys. We succinctly present a procedure to select the weights from these data sources.<sup>3</sup> Importantly, this procedure accounts for the fact that the weights of multidimensional poverty measures are not marginal weights of substitution. This fact implies that seemingly natural procedures are not fit for purpose.<sup>4</sup> The second is to switch the unit of analysis from the household level to the individual level as soon as some variables are collected at individual level. We discuss the advantages of this switch as well as its associated misinterpretation risk.

The third source of potential improvements relates to the way in which the indicator is used. Merely reporting that monetary poor individuals tend to cumulate non-monetary deprivations gives the impression that the exercise has no added value. Multidimensional

> 3To be sure, it is possible to use fixed weights even when their value is selected from information on preferences.

> 4Multidimensional poverty measures will make incorrect well-being comparisons when the values for their weights are selected to correspond to marginal rates of substitution.

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