towards understanding the impact of the international financial crisis on child poverty in south...
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Towards understanding the impact of the international financial crisis on child poverty in South Africa: The child poverty context
Ramos Mabugu*, Debra Shepherd** and Servaas van der Berg**with
Margaret Chitiga°, Bernard Decaluwé°°, Hélène Maisonnave*, Véronique Robichaud°°, Judith Streak** and Dieter von Fintel**
* Financial and Fiscal Commission, South Africa** University of Stellenbosch° University of Pretoria °° Laval University (Québec) and PEP network
Draft paper to Unicef/ODI conference, London, November 2009
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Introduction
• Macro-micro study: – CGE model uses micro-econometrically
determined elasticities – Micro-simulations use CGE outputs
• Issues covered here:– Child poverty profile– Child Support Grant as major instrument to
combat child poverty– CGE model and its results– Possible implications for poverty
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Poverty profile• Stochastic poverty dominance for most dimensions • Adult equivalence scale does not much affect poverty
profile• Thus use per capita income at 40th percentile as
poverty line• 52.9% of population poor: 65.5% of all children (11.8
million)• Differentials larger for P1 and P2 – thus lower poverty
line would increase child-adult poverty differential• Poverty largest amongst youngest, blacks, rural areas,
poorer provinces• Reported hunger strongly declined – probably
because of Child Support Grants (CSGs) and other grants (employment growth played only a small role)
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Poverty profile for children and adults (poverty line at 40th percentile of household per capita income)
Child poverty (0-17 years)
P0 Poverty headcount rate P1 Poverty depth measure
P2 Poverty severity measure
Rate (%) Number
Age 0-4 66.1 3 066 509 0.336 0.213
5-14 65.7 6 681 507 0.343 0.202
15-17 63.8 2 067 609 0.332 0.203
0-17 (all children) 65.5 11 822 544 0.328 0.205
18+ (all adults) 45.2 0.213 0.126
Racial groupBlack 72.5 11 100 826 0.375 0.232
Coloured 41.3 623 412 0.167 0.093Asian 24.2 76 137 0.093 0.052White 2.0 18 081 0.012 0.008
Urban/Rural location
Rural 82.8 7 376 451 0.446 0.28Urban 48.6 4 442 491 0.226 0.133
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Households that reported that children went hungry in the past year
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Child Support Grants
• Introduced 1998, expanded rapidly– Growing coverage within age-eligible groups– Age-eligibility increased from 7 to 15 years
• Quite good targeting – but puzzlingly large errors of exclusion
• Reduced poverty in period of good growth• Hypothesis: CSF acts as a form of income
diversification that mitigates impact of economic shocks on vulnerable children
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Contribution of spending on each type of social grant to total social grant spending
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CSG: Eligibility and coverageGHS Eligible
age
Recipients of CSG Pop. of eligible
age[D]
Coverage rate
[A]/[D]Of eligible age [A]
Not of eligible age [B]
Total[C]
2003 0-8 years 2 241 760 321 534 2 563 294 8 299 039 27.0%
2004 0-10 years 4 201 481 175 526 4 377 007 11 100 241 37.9%
2005 0-13 years 5 702 793 139 043 5 841 836 14 052 170 40.6%
2006 0-13 years 6 459 760 265 579 6 725 339 14 152 509 45.6%
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CSG roll-out: Progression over time in CSG coverage rates in households by earnings decile of the employed
0%
10%
20%
30%
40%
50%
60%
70%
Decile1 Decile2 Decile3 Decile4 Decile5 Decile6 Decile7 Decile8 Decile9 Decile10 GHS2002 GHS2003 GHS2004 GHS2005 GHS2006
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Economic crisis and modelling its impact
• SA’s first recession in 17 years• Cumulative job losses 1 million• Two scenarios modelled in CGE model:
– Moderate (growth picks up from end 2009)– Severe (protracted global slowdown)
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IMF Growth Projections for South Africa (estimates after 2008)
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Potential effect of CSG and job losses on FGT poverty measures (2008 = base year)
(provisional results)P0
Headcount Poverty rate
P1
Poverty Gap ratio
P2
Squared Poverty
Gap ratioBaseline 2008 Child with CSG 0.686 0.417 0.304
Child without CSG 0.721 0.509 0.422
2009: 1.2 million job losses
Child with CSG 0.706 0.445 0.331
Child without CSG 0.736 0.538 0.454
Note: CSG has larger effect than employment
In economic boom, similar results held: employment contributed little to poverty decline
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Static effect of CSG on child poverty headcount
0.2
.4.6
.8
0 500 1000 1500
Total Income 08 Total Income 08 no CSG
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Effect of 1.2 million job loss on child poverty headcount
0.2
.4.6
.8
0 500 1000 1500
Total Income 08 Total Income 09
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Elasticities and effect of prices
• Prices derived in modelling NIDS data• Urban-rural poverty differential narrows when
using these prices• Generally high price elasticities mean much
substitution following price rises• However, low price elasticity for staple
(maize) impacts on consumption volumes
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Poverty adjusted for price differentials: Early estimates
Headcount poverty rate Urban Rural Total
Households 0.395 0.480 0.434
All individual level 0.463 0.513 0.489
• Children 0.495 0.531 0.516
• Adults 0.434 0.498 0.465
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Provisional conclusion• Economic crisis may not have completely
reversed progress in child poverty that resulted from expansion of CSG in recent growth period
• Yet the crisis ended the period of declining child poverty and hunger
• Non-money metric impact probably more limited, due to structure of SA service provision (e.g. education free for poor, public health largely free)