_Table 4: Impact of two deprivations statuses (extreme and moderate) on poverty rates, baseline scenario_

||**Others-**<br>**dimensions poor**<br>**(%)**|**National poverty headco**<br>**Omitted**<br>**poor**<br>**(%)**|**unts**<br>**Consistently**<br>**poor**<br>**(%)**|
|---|---|---|---|
|Extreme deprivation considered|27.9|11.4|16.5|
|All non-monetary deprivations are||||
|assumed moderate|16.2|6.7|9.5|

_Source:_ Authors’ estimates based on data from NLSS 2019 _Note_ : The table presents other-dimensions poverty rates in Nigeria i) under the baseline scenario, ie, when the two-thresholds cutoffs (extreme and moderate deprivation) are applied for each non-monetary dimension and ii) under a modification of the baseline deprivation mapping such that only a one-threshold cutoff is applied for each non-monetary deprivation (that is, only the moderate deprivation status is considered: any extreme non-monetary deprivation is converted into a moderate deprivation). The overall other-dimensions poverty is decomposed into omitted poor and consistently poor to account for individuals who are both monetary and other-dimensions poor.

# **Section 4.3: Incidence of low well-being (quantity and quality of life)**

We focus in this subsection on the values taken by PALE, our well-being indicator that aggregates quantity and quality of life. Our objective is to get a sense of the impact of accounting for the direct impact of mortality when measuring low well-being as well as the impact of the value selected for the normative weight given to mortality. We first contrast PALE, which accounts for both quantity and quality of life, with H, which only accounts for quality of life. Then, we probe the relative importance of mortality and other dimensions of deprivations in determining low well-being.

## **PALE and its normative weight**

We begin by illustrating how our well-being indicator aggregates the direct impact of mortality with quality of life. Figure 9 provides a scatter plot that shows for each Nigerian state the value of PALE on the vertical-axis as a function of the (multidimensional) head-count ratio H on the horizontal axis. Recalling that by definition P P is obtained by “scaling down” its value for life-expectancy at birth (LE). This scaling down is more θθ<sup>= P∗ (1 − θθ ∗ HH), the figure illustrates that the value for PALE for a given state</sup> pronounced when the head-count ratio H is larger and when the weight given to mortality is smaller, i.e., the value for is larger. Consider for instance our baseline design, which conservatively assumes the largest value for compatible with the idea that being (multidimensionally) poor is not worse than being dead ( ) and which is illustrated in Figure 9. The value for PALE of any given state is thus θθ P P 1 = P , meaning that LE is scaled down by (1-H). A state with a small head-count ratio has its value θθ θθ = 1 of PALE that is close to its value of LE. Intuitively, a newborn in such a state is expected to live most of his ∗ (1 − HH) life out of poverty, assuming poverty and mortality remain constant. Such newborn is “expected” to live 40 years free from poverty if her life-expectancy at birth is 50 years and the head-count ratio is 20 percent. The perspective looks grimmer for a newborn whose life-expectancy at birth is 45 years and whose state has a head-count ratio of 90 percent because she then is “expected” to live only 4.5 years free from poverty.

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