Presentation from AIR, UNC and Palm Associates on the evidence of cash transfer sin Zambia

1. THE IMPACT OF SOCIAL
CASH TRANSFERS IN
ZAMBIA
David Seidenfeld (AIR)
Ashu Handa (UNC)
Gelson Tembo (Palm Associates)
May 2016
Lusaka, Zambia

2. Manda Hill 2010

3. Manda Hill 2014

4. And then another mall. . .

5. 2010 Chipolopolo Ranked 14th in Africa

6. 2012 Africa Cup Champions

7. 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

8. 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

9. MCDSW commissioned ‘gold standard’
evaluations of these two programmes 2010-2014
Child Grant Program
N=2500
Treatment Group=1250
Control Group=1250
Multiple Category
Targeted Program
N=3000
Treatment Group=1500
Control Group=1500
2010 Baseline
2011 Baseline
2012 24m follow-up
2013 30m follow-up (harvest) 24m follow-up
2013 36m (lean)
2014 48m follow-up 36m follow-up
Additional features
Longitudinal cluster randomized control trials

10. 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)

11. Very different demographic profile of
households in MCTG and CGP
0.02.04.06.08.1
Density
0 20 40 60 80 100
Age in years
0
.02.04.06.08
.1
Density
0 20 40 60 80 100
Age in years
MCTG CGP
preschoolers
adolescents
elderly care-givers
prime-age adults

12. Targeting: Baseline extreme poverty rates
much higher than rural households
65
95.5
91
0
10
20
30
40
50
60
70
80
90
100
Extreme Poverty
Extreme Poverty Rates of Beneficiaries at Baseline
All Zambia Rural CGP MCTG

13. Targeting: Beneficiaries much more food
insecure than all rural households
5.36
21.13
28.1
0
5
10
15
20
25
30
35
40
45
50
<2 meals per day
Percentage eating <2 meals per day
All Zambia Rural CGP MCTG

14. Core methodology: Compare trend in
control group vs. trend in treatment group
30
35
40
45
50
55
60
65
70
75
80
Baseline 24-months 30-months 36-months 48-months
Per capita consumption ZMW – CGP evaluation sample
Treatment Control
Subtract this portion to get net effect of program
Net impact of program

15. 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?

16. How is the money spent?
Spent on necessities?
Or
Wasted on alcohol and
tobacco?

17. Impacts on total consumption: K12-16
increase (31 percent)
20
30
40
50
60
70
80
90
Baseline 24m 36m 48m
CGP 2010 Kwacha
Treatment Control
20
30
40
50
60
70
80
90
Baseline 24m 36m
MCTG 2011 Kwacha
Treatment Control

18. Impacts on food consumption: K10-12
increase (28% CGP) (35% MCTG)
0
10
20
30
40
50
60
70
Baseline 24m 36m 48m
CGP 2010 Kwacha
Treatment Control
0
10
20
30
40
50
60
70
Baseline 24m 36m
MCTG 2011 Kwacha
Treatment Control

19. Impacts on food security-percent
consuming 1+ meals per day
50
55
60
65
70
75
80
85
90
95
100
Baseline 24m 36m 48m
CGP 2010 Kwacha
Treatment Control
50
55
60
65
70
75
80
85
90
95
100
Baseline 24m 36m
MCTG 2011 Kwacha
Treatment Control

20. Impacts on monetary poverty gap: 10-12
percentage point decrease
20
30
40
50
60
70
80
Baseline 24m 36m 48m
CGP 2010 Kwacha
Treatment Control
20
30
40
50
60
70
80
Baseline 24m 36m
MCTG 2011 Kwacha
Treatment Control

21. What was consumed? Mostly food, then health
and education (8%). In CGP, transport and
communication (11%)
72%
8%
5%
11%
4%
CGP
Food
Health, Educ
Clothing
Transport, Comm
Other
84%
8%
3%
1%
4%
MCTG

22. Impact on food expenditures dominated
by cereals, meat/dairy, oil and sugar
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Cereals Pulses Meat, dairy Fruit, veggie Fats, oil,
sugars
CGP
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Cereals Pulses Meat, dairy Fruit, veggie Fats, oil,
sugars
MCTG
Increase in diet diversity, more proteins and fats being consumed

23. 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

24. Productivity
Do People Invest the Money?
Or
Treat Money as a Handout?

25. Impacts on number of goats: 158%
increase in CGP, 195% increase in MCTG
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Baseline 24m 36m
CGP
Treatment Control
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Baseline 24m 36m
MCTG
Treatment Control

26. Impacts on number of chickens: 80%
increase in CGP, 71% increase in MCTG
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Baseline 24m 36m
CGP
Treatment Control
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Baseline 24m 36m
MCTG
Treatment Control

27. Is this a ‘hand-out’, or is cash put to good use?
Impacts on agricultural spending, savings…
0
20
40
60
80
100
120
140
160
180
Crop expenditure Any savings Amount saved
Percent impact at 36-months
CGP MCTG

28. 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

29. Fertility
Do Families in the CGP have
more children to remain
eligible?

30. 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

31. What about the kids?

32. Positive impacts on school enrollment
among secondary age children
.2.3.4.5.6.7.8.9
schoolenrollmentproportion
6 8 10 12 14 16 18
person's age in years
Control Treatment
MCTG Wave 3 School Enrollment
.2.3.4.5.6.7.8.9
6 8 10 12 14 16 18
person's age in years
Control Treatment
CGP Wave 3 School Enrollment
9 point impact
6 point impact
12 point impact
By 36-months beneficiary children age 11+ more likely to be enrolled in school

33. Grade 3 math test – Serenje District, Zambia
More kids in school but school quality still a challenge

34. Households purchased, shoes, clothes,
blankets for children: +20 point impact in children
5-17 having all three items
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Baseline 24-months 36-months
CGP
Control Treatment
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Baseline 24-months 36-months
MCTG

35. 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

36. Health Facilities Poorly Stocked

37. How Do the Two Programs Compare?
•Same transfer size
•Different demographics
•Same time-frame

38. Despite the different target groups,
overall impacts are surprisingly
similar
•Key common characteristic is that
households are ultra-poor

39. 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 .8
Effect size in SDs units for comparability
36-month results at a glance
Impacts from both programs similarMCTG
CGP

40. Benefit to household larger than the value
of transfer—multiplier effects!
MCTG CGP
Annual value of transfer (A) 720 660
Savings 10 61
Loan repayment 23 27
Consumption 966 800
Livestock value 183 48
Productive tools value 25 50
Total spending (consumption + spending) (B) 1202 986
Estimated 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.

41. What is the cost to scale-up? Is it affordable
Simulations show in Zambia, with 20% coverage, cost is 1% of GDP, 4% of budget
0%
5%
10%
15%
20%
Congo,DemocraticRepublic
Zimbabwe
Burundi
Liberia
Eritrea
Niger
Malawi
CentralAfricanRepublic
Madagascar
Mali
Togo
Guinea
SouthSudan
Mozambique
Guinea-Bissau
Comoros
Ethiopia
SierraLeone
BurkinaFaso
Uganda
Rwanda
Benin
Tanzania,UnitedRepublicof
Zambia
Côted'Ivoire
Kenya
TheGambia
Senegal
Mauritania
SaoTomeandPrincipe
Lesotho
Cameroon
Chad
Sudan
Djibouti
Nigeria
Ghana
CapeVerde
CongoBrazzaville
Swaziland
Angola
Namibia
SouthAfrica
Mauritius
Botswana
Gabon
Seychelles
EquatorialGuinea
Socialcashtransferexpenditureestimates
In % of general government total expenditure
In % of GDP

42. 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

43. 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?

44. extras

45. Low Attrition (< 4%) = Maintain Validity
Palm Associates

46. Many Young Children in Study > 2,500
children under 3 years old at baseline

47. ACKNOWLEDGEMENTS
Funding/Mandate
Ministry of Community Development, Mother and Child
Health (MCDCH)
UNICEF
DFID
Irish Aid
GTZ/GIZ
Impact Evaluation
American Institutes for Research (AIR)
Palm Associates Limited (PAL)
University of North Carolina (UNC)

48. Contact Information
• David Seidenfeld (AIR) dseidenfeld@air.org
• Ashu Handa (UNC) shanda@email.unc.edu
• Gelson Tembo (Palm Associates) tembogel@gmail.com