for both H and PALE. To give a sense of the correlation between rankings among less dissimilar states, we also compute the fraction of re-rankings between states that have less than 50 percent poverty and the fraction of re-rankings between states that have more than 50 percent poverty. For instance, the fraction of re-raking between monetary poverty and mean consumption are 10 percent and 8 percent, respectively in the former and latter subset of states.

_Table 5: Percentage of states pairwise comparisons reversed between pairs of well-being indicators_

|||**Baseline**|||**Preferred**||
|---|---|---|---|---|---|---|
|<br>|**All states**|**States with**<br>HM**<50**|**States with**<br>HM**>=50**|**All states**|**States with**<br>HM**<50**|**States with**<br>HM**>=50**|
|Average consumption -VS-HM<br> <br>|5%|<br>10%|<br>8%|5%|<br>10%|<br>8%|
|<br>HM-VS- PALE<br> <br>|7%|17%|12%|14%|29%|23%|
|<br> <br>HM-VS-H<br>|7%|16%|13%|9%|22%|13%|
|<br> <br>H-VS- PALE|3%|8%|4%|10%|17%|19%|
|<br> <br>_Source:_Authors’ estimates based on data from<br>_Note_: The table shows the percentage of pairs<br>consumption, monetary poverty rate (HM),mu<br>for each scenario, baseline and preferred. For<br>rate below 50%, on the one hand, and those w<br>the disparity between compared states.|NLSS 2019<br>of states whose c<br>ltidimensional po<br>each scenario, re<br>ith a monetary p|omparison is rever<br>verty rate (H) and p<br>strictions are applie<br>overty rate above 5|sed between two dif<br>overty-adjusted life-e<br>d in order to consid<br>0%, on the other. Th|ferent well-being<br>xpectancy (PALE). <br>er only states with<br>e aim of these res|indicators: average<br>Results are presented<br>a monetary poverty<br>trictions is to reduce|<br> <br>|

Second, when comparing monetary poverty and (baseline) PALE, the fraction of re-rankings is 7 percent. This fraction increases to 17 percent (12 percent) when restricting comparisons to the subset of states that have less (more) than 50 percent monetary poverty. Those frequencies of re-rankings are arguably substantial given that PALE accounts for monetary poverty. The table suggests that, in the baseline scenario, moving from monetary poverty to multidimensional poverty generates more re-rankings than moving from multidimensional poverty to PALE. This reflects the fact that (1) mortality is less heterogeneous across states than other-dimensions poverty and, to a lesser extent, (2) mortality is more correlated with monetary poverty than security deprivations.

Third, the preferred design implies more frequent re-rankings than the baseline design. When comparing monetary poverty and (preferred) PALE, the fraction of re-rankings on the whole set of states increases to 14 percent. This fraction further increases to 29 percent (23 percent) when restricting comparisons to the subset of states that have less (more) than 50 percent monetary poverty, which arguably are very substantial re-rankings (recall that PALE accounts for monetary poverty). The table suggests that the more frequent re-rankings when moving from the baseline to the preferred design are mostly due to the larger normative weight given to mortality. Indeed, re-rankings between these two designs do not increase as much when comparing monetary poverty and multidimensional poverty, whereas they increase very substantially when comparing multidimensional poverty and PALE. This highlights the need to better understand the plausible values for this normative weight.

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