Upload
michelle-mills
View
100
Download
0
Embed Size (px)
Citation preview
THE IMPACT OF SOCIAL CASH TRANSFERS IN
ZAMBIADavid Seidenfeld (AIR)
Ashu Handa (UNC)Gelson Tembo (Palm Associates)
May 2016Lusaka, Zambia
Manda Hill 2010
Manda Hill 2014
And then another mall. . .
2010 Chipolopolo Ranked 14th in Africa
2012 Africa Cup Champions
The Child Grant Program-CGP- Started in 2010
- Households with a child under 3 enrolled
- Unconditional
- 55 Kwacha per month (increased over time)
- No differentiation by household size
The Multiple Category Targeted Program - MCTG
- Started in 2011
- Widow headed w/orphans; Elderly headed w/orphans; Disabled members
- Unconditional
- 60 Kwacha per month (increased over time)
- No differentiation by household size
MCDSW commissioned ‘gold standard’ evaluations of these two programmes 2010-2014
Child Grant Program N=2500
Treatment Group=1250Control Group=1250
Multiple Category Targeted Program
N=3000Treatment Group=1500
Control Group=1500
2010 Baseline2011 Baseline2012 24m follow-up2013 30m follow-up (harvest) 24m follow-up2013 36m (lean)2014 48m follow-up 36m follow-up
Additional featuresLongitudinal cluster randomized control trials
CGP, MCTG Districts highly isolated, Greatest Levels of Poverty(Travel Time from Lusaka by Vehicle)
Kaputa(20 Hrs)
Kalabo(12 Hrs)
Shangombo(16 Hrs)
Luwingu(18 Hrs)
Serenje(12 Hrs)
Very different demographic profile of households in MCTG and CGP
0.0
2.0
4.0
6.0
8.1
Den
sity
0 20 40 60 80 100Age in years
0.0
2.0
4.0
6.0
8.1
Den
sity
0 20 40 60 80 100Age in years
MCTG CGPpreschoolers
adolescents
elderly care-giversprime-age adults
Targeting: Baseline extreme poverty rates much higher than rural households
Extreme Poverty0
10
20
30
40
50
60
70
80
90
100
65
95.591
Extreme Poverty Rates of Beneficiaries at Baseline
All Zambia Rural CGP MCTG
Targeting: Beneficiaries much more food insecure than all rural households
<2 meals per day0
5
10
15
20
25
30
35
40
45
50
5.36
21.13
28.1
Percentage eating <2 meals per day
All Zambia Rural CGP MCTG
Core methodology: Compare trend in control group vs. trend in treatment group
Baseline 24-months 30-months 36-months 48-months30
35
40
45
50
55
60
65
70
75
80
Per capita consumption ZMW – CGP evaluation sample
Treatment Control
Subtract this portion to get net effect of program
Net impact of program
Presentation overview: address major questions with giving cash to poor households
• How is the money spent? • Do people invest the money?• Do people have more children to remain eligible?
• How much does it cost? Can a country like Zambia afford cash transfers?
How is the money spent?
Spent on necessities?Or
Wasted on alcohol and tobacco?
Impacts on total consumption: K12-16 increase (31 percent)
Baseline 24m 36m 48m20
30
40
50
60
70
80
90
CGP 2010 Kwacha
Treatment Control
Baseline 24m 36m20
30
40
50
60
70
80
90
MCTG 2011 Kwacha
Treatment Control
Impacts on food consumption: K10-12 increase (28% CGP) (35% MCTG)
Baseline 24m 36m 48m0
10
20
30
40
50
60
70
CGP 2010 Kwacha
Treatment Control
Baseline 24m 36m0
10
20
30
40
50
60
70
MCTG 2011 Kwacha
Treatment Control
Impacts on food security-percent consuming 1+ meals per day
Baseline 24m 36m 48m50
55
60
65
70
75
80
85
90
95
100
CGP 2010 Kwacha
Treatment Control
Baseline 24m 36m50
55
60
65
70
75
80
85
90
95
100
MCTG 2011 Kwacha
Treatment Control
Impacts on monetary poverty gap: 10-12 percentage point decrease
Baseline 24m 36m 48m20
30
40
50
60
70
80
CGP 2010 Kwacha
Treatment Control
Baseline 24m 36m20
30
40
50
60
70
80
MCTG 2011 Kwacha
Treatment Control
What was consumed? Mostly food, then health and education (8%). In CGP, transport and communication (11%)
72%
8%
5%
11%
4%
CGP
FoodHealth, EducClothingTransport, CommOther
84%
9%
3% 1%4%
MCTG
Impact on food expenditures dominated by cereals, meat/dairy, oil and sugar
Cereals Pulses Meat, dairy Fruit, veggie Fats, oil, sugars
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
CGP
Cereals Pulses Meat, dairy Fruit, veggie
Fats, oil, sugars
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
MCTG
Increase in diet diversity, more proteins and fats being consumed
No evidence cash is ‘wasted’ on alcohol & tobacco
Alcohol/tobacco represent 1% of budget share No positive impacts found on alcohol/tobacco:
Data comes from detailed consumption module covering over 200 individual items, so hard to lie on just these items
Alternative measurement approaches yield same result: “Has alcohol consumption increased in this community
over the last year?” “Is alcohol consumption a problem in your community?” No differences between Treatment and Control group on
these responses
Productivity
Do People Invest the Money? Or
Treat Money as a Handout?
Impacts on number of goats: 158% increase in CGP, 195% increase in MCTG
Baseline 24m 36m0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
CGP
Treatment Control
Baseline 24m 36m0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
MCTG
Treatment Control
Impacts on number of chickens: 80% increase in CGP, 71% increase in MCTG
Baseline 24m 36m0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
CGP
Treatment Control
Baseline 24m 36m0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
MCTG
Treatment Control
Is this a ‘hand-out’, or is cash put to good use? Impacts on agricultural spending, savings…
Crop expenditure Any savings Amount saved0
20
40
60
80
100
120
140
160
180
Percent impact at 36-months
CGP MCTG
Other economic impacts…• Value of harvest increased significantly for both programs
• CGP: More time devoted to own-farm, more crop sold• MCTG: More hired labor
• Non-farm enterprise increased significantly for both programs• CGP: Much larger impacts (+12pp), mostly women-operated
businesses• MCTG: Smaller impacts (+4pp)
• Pattern of effects consistent with household type• CGP more prime-age workers• MCTG labor constrained so hired labor to work farm
Fertility
Do Families in the CGP have more children to remain
eligible?
No Increase in Children• Outcomes
• total fertility, currently pregnant, ever pregnant, whether had still birth/miscarriage
• Analysis samples• All women in household, women <25 years of age, intended
beneficiary only• No evidence that fertility increased for any outcome or any
group• Weak evidence of reduction in miscarriage and still births• “Unconditional government social cash transfer in Africa does not
increase fertility” J of Population Economics 2016• http://link.springer.com/article/10.1007/s00148-016-0596-x
What about the kids?
Positive impacts on school enrollment among secondary age children
.2.3
.4.5
.6.7
.8.9
scho
ol e
nrol
lmen
t pro
porti
on
6 8 10 12 14 16 18person's age in years
Control Treatment
MCTG Wave 3 School Enrollment
.2.3
.4.5
.6.7
.8.9
scho
ol e
nrol
lmen
t pro
porti
on
6 8 10 12 14 16 18person's age in years
Control Treatment
CGP Wave 3 School Enrollment
9 point impact6 point impact
12 point impact
By 36-months beneficiary children age 11+ more likely to be enrolled in school
Grade 3 math test – Serenje District, ZambiaMore kids in school but school quality still a challenge
Households purchased, shoes, clothes, blankets for children: +20 point impact in children 5-17 having all three items
Baseline 24-months 36-months0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
CGP
Control Treatment
Baseline 24-months 36-months0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
MCTG
Program Limited by Supply of Social Services
•No Impacts on Child Nutrition•No Impacts on Child Health
• Over 50% of health facilities in CGP districts are health posts or dispensaries (32 facilities total)
• Less than 20% of health facilities have at least one registered nurse on staff
Health Facilities Poorly Stocked
How Do the Two Programs Compare?
•Same transfer size
•Different demographics
•Same time-frame
Despite the different target groups, overall impacts are surprisingly similar•Key common characteristic is that households are ultra-poor
Total consumption pc
Food security scale (HFIAS)
Overall asset index
Relative poverty index
Incomes & Revenues index
Finance & Debt index
Material needs index (5-17)
Schooling index (11-17)
Anthropometric index (0-59m)
-.2 0 .2 .4 .6 .8Effect size in SDs units for comparability
36-month results at a glanceImpacts from both programs similarMCTG
CGP
Benefit to household larger than the value of transfer—multiplier effects!
MCTG CGPAnnual value of transfer (A) 720 660Savings 10 61Loan repayment 23 27Consumption 966 800Livestock value 183 48Productive tools value 25 50Total spending (consumption + spending) (B) 1202 986Estimated multiplier (B/A) 1.67 1.49
Impacts are based on econometric results and averaged across all follow-up surveys.Estimates for productive tools and livestock derived by multiplying average increase (numbers) by market price. Only statistically significant impacts are considered.
What is the cost to scale-up? Is it affordableSimulations show in Zambia, with 20% coverage, cost is 1% of GDP, 4% of budget
0%
5%
10%
15%
20%
In % of general government total expenditureIn % of GDP
Soci
al c
ash
trans
fer e
xpen
ditu
re e
stim
ates
Not a Handout = Does NOT Create Dependency
• Increased Productive Activity•No Evidence of Increased Fertility•No Impact on Alcohol Consumption• Improved Standard of Living•Children in school, materially better off•Cash creates multipliers, allows the poorest to raise their income
Discussion• Do cash transfers deserve to be considered part of an inclusive growth strategy for Zambia?• What are the doubts
• Is K70 per month enough to pull households permanently out of poverty? • If cash withdrawn, what would happen to these
households?• Can these impacts be enhanced? How? With what other services?
extras
Low Attrition (< 4%) = Maintain ValidityPalm Associates
Many Young Children in Study > 2,500 children under 3 years old at baseline
ACKNOWLEDGEMENTSFunding/Mandate
Ministry of Community Development, Mother and Child Health (MCDCH)UNICEFDFIDIrish AidGTZ/GIZ
Impact EvaluationAmerican Institutes for Research (AIR)Palm Associates Limited (PAL)University of North Carolina (UNC)
Contact Information• David Seidenfeld (AIR) [email protected]• Ashu Handa (UNC) [email protected]• Gelson Tembo (Palm Associates) [email protected]