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Great new @CGDev WP on #Gender, Headship & Poverty in #Africa by @caitbrownecon & @DominiquePVDW. I had the pleasure of reading this a few months back -- here is what I learned:
Thread /n
https://twitter.com/caitbrownecon/status/1250108229306257408
Thread /n
https://twitter.com/caitbrownecon/status/1250108229306257408
They revisit an old debate with new data & analysis – they ask:
Are FHH poorer than MHHs (in Africa)?
& Is headship even a useful measure to use (for this question & more generally?) 2/n
Bonus: Recap of @CGDev event on this topic w/ @agnesquis : https://www.cgdev.org/blog/how-significant-household-headship-agnes-quisumbing-and-dominique-van-de-walle-cgd-podcast
Are FHH poorer than MHHs (in Africa)?
& Is headship even a useful measure to use (for this question & more generally?) 2/n
Bonus: Recap of @CGDev event on this topic w/ @agnesquis : https://www.cgdev.org/blog/how-significant-household-headship-agnes-quisumbing-and-dominique-van-de-walle-cgd-podcast
Using PovcalNet data from 43 countries, they show descriptive trends in #headship across countries. Overall 18% of pop lives in FHH, w/ wide variation – e.g. Southern Africa has 43% & West Africa has 13%. Also higher share in urban areas.
Fascinating descriptives! 3/n
Fascinating descriptives! 3/n
A key theme of the paper is the role marital status plays – FHH are diverse & this matters for poverty and wellbeing.
Only 25% of female heads are married vs. 83% of male heads – female heads are mostly widows & divorcees (64% of all female heads). 4/n
Only 25% of female heads are married vs. 83% of male heads – female heads are mostly widows & divorcees (64% of all female heads). 4/n
Another key theme is HH composition.
Using LSMS data, they show that FHH have higher proportion female members, are smaller is size, & more likely to be labor constrained, higher dependency ratios (latter among those w/o adult male).
These details matter. 5/n
Using LSMS data, they show that FHH have higher proportion female members, are smaller is size, & more likely to be labor constrained, higher dependency ratios (latter among those w/o adult male).
These details matter. 5/n
Are FHHs poorer?
On average, using standard measures *no*, they are actually *less* likely to be poor across all three poverty measures (FGD, headcount, poverty gap, sq poverty gap). However, this is not true in all regions, e.g. in southern Africa they are.
6/n
On average, using standard measures *no*, they are actually *less* likely to be poor across all three poverty measures (FGD, headcount, poverty gap, sq poverty gap). However, this is not true in all regions, e.g. in southern Africa they are.
6/n
However, these conclusions do not hold when taking into account “modest” economies of scale that larger (MHH) face. In addition, when comparing divorced/widowed HHHs, FHHs are worse off.
Nice graphic shows var in economies of scale [positive = FHH higher poverty rate] 7/n
![However, these conclusions do not hold when taking into account “modest” economies of scale that larger (MHH) face. In addition, when comparing divorced/widowed HHHs, FHHs are worse off.Nice graphic shows var in economies of scale [positive = FHH higher poverty rate] 7/n](https://pbs.twimg.com/media/EVl6QEoU0AAFXVh.png "However, these conclusions do not hold when taking into account “modest” economies of scale that larger (MHH) face. In addition, when comparing divorced/widowed HHHs, FHHs are worse off.Nice graphic shows var in economies of scale [positive = FHH higher poverty rate] 7/n")
Nice graphic shows var in economies of scale [positive = FHH higher poverty rate] 7/n
Many takeaways, but one for me was the difficulty of strictly using poverty rates to target vulnerability 4 #socialprotection, & importance of taking into account HH size/composition.
Also useful 4 rapid targeting in #COVID19 [we've already cited in forthcoming brief] /end
Also useful 4 rapid targeting in #COVID19 [we've already cited in forthcoming brief] /end
