weight _θ >_ 0, which captures the trade-off between poverty and mortality, corresponds to the fraction of the period utility lost when poor. When being poor has no utility cost, _θ_ takes the value zero and _PALE_ 0 corresponds to life expectancy at birth. When being poor (for one year) is as bad as losing one year of life, _θ_ = 1 and our index _PALE_ 1 then corresponds to the poverty-free life expectancy at birth (Riumallo-Herl et al., 2018), i.e. the number of years of life a newborn expects to live out of poverty. _PALEθ_ does not suffer from the mortality paradox as long as _θ ≤_ 1. Besides its theoretical properties, _PALEθ_ enjoys two practical advantages. First, its data-requirement are minimal as only the life-expectancy at birth and the poverty head-count ratio are necessary. Second, _PALEθ_ has a simple interpretation, as it measures the equivalent number of years of life spent out of poverty.

In a second step, we show how to generalize _PALEθ_ to account for the distribution of lifespans. More precisely, _PALEθ_ lends itself to the definition of a new indicator, which is consistent with the minimalist view. This requires the introduction of a normative age threshold ˆ _a_ , which corresponds to our definition of premature mortality. This new index, which we call the _expected_ deprivation index ( _EDθa_ ˆ), is the weighted sum of the number of years that a newborn expects to lose prematurely or to spend in poverty, using the same weight as in _PALEθ_ .<sup>6</sup> We call the index _expected_ deprivation, given its proximity to the concept of life expectancy in its construction, interpretation and assumptions.

To measure the real world relevance of our indexes, we combine data sets provided by the World Bank data on income poverty (Poverty and Inequality Platform (World Bank, 2023)) and an internationally comparable data set on mortality data (Global Burden of Disease Collaborative Network, 2020) from 1990 to 2019. We show that mortality is growing in relative importance and substantially affects global poverty comparisons: during the 2005-2019 period, at least 34% of PALE’s growth was due to the growth of life expectancy, as opposed to 17% from 1991 to 2004. For all possible values of _θ_ , _PALEθ_ is able to solve in 2019 about half of the between country and 40% of the within country comparisons when focusing on these comparisons for which life expectancy and headcount are conflicting.

**Literature review** Baland et al. (2021) proposed a way of integrating mortality into poverty measurement that is consistent with the minimalist view. They observe that an integrated indicator should at least meaningfully compare _stationary_ societies, for which natality, mortality and poverty are constant over time. (In stationary societies, the outcomes observed in a given year completely reflect the life-cycle effects of their mortality.) They show that such indicators satisfy a set of basic axioms when based on a weighted sum of a number of years of life prematurely lost and a number of years of life spent in poverty.

We improve on _GDθa_ ˆ, the main indicator proposed by Baland et al. (2021), along the following dimensions. First, given an age threshold ˆ _a_ , the death of a poor individˆ ual above the age of _a_ is considered by _GDθa_ ˆ as an improvement. The “minimalist” view taken by this measure therefore implies a form a mortality paradox. Second, _GDθa_ ˆ is not straightforward to interpret, preventing its widespread diffusion in pub-

> 6Again, this implies that a newborn is expected to be exposed throughout her lifespan to the poverty and mortality observed in the current period.

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