Solomon Asfaw, PhD Principal Evaluation Officer Independent Evaluation Unit (IEU) Green Climate Fund (GCF) October 26, 2018, South Korea

1. Impact of CashTransfer Programs in Building
Resilience: Insight from African Countries
Independent Evaluation Unit (IEU)
Green Climate Fund (GCF)
October 26, 2018, South Korea
Solomon Asfaw, PhD
Principal Evaluation Officer

2. Outline
1. Background of CT in SSA
2. Why do we expect resilience impact?
3. What does the evidence say?
4. Final remark

3. Preview: Risk matters
Production
risk
Price risk
 Climate,
 Pests,
 Fire, etc.
 Imported price volatility
 Natural price volatility
 Endogenous price
volatility
HR risks
Regulation
risks
Financial risks
Revenue
instability
 Reduction of
investment within
food production in
composition and
volume
 Reduction of
consumption and
investment in other
non-food activities
of households
 Access to credit
 Credit costs
 Change in policies/norms
(health, environment,
etc.)
 Diseases / disabilities
3

4. How to manage risks and food
insecurity?
 Activities designed to reduce the likelihood of an adverse event or
reduce the severity of actual losses
(e.g. Irrigation, use of resistant seeds; improved early warning
system; adoption of better agronomic practices etc.)
MITIGATE
TRANSFER
COPE
1
2
3
 This entails the transfer of risk to a willing party, for a fee or
premium.
(e.g. Commercial insurance and hedging etc.)
 This involves improving resilience to withstand and cope with
events
(e.g. social safety nets, buffer funds, savings, strategic
reserves etc.)
4

5.  Approximately half of the countries of SSA have some
kind of government-run CT program
• And others have multilateral/NGO-run CT programs
 Some programs are national
• Others scaling up
• Some pilots beginning this year
 Beneficiaries predominately rural, most engaged in
agriculture
Expansion of cash transfer programs in
Sub-Saharan Africa

6. What’s particular about
cash transfers in SSA--context
 HIV/AIDS
• Economic and social vulnerability
 Widespread poverty
 Continued reliance on subsistence agriculture and
informal economy
• Exit path from poverty is not necessarily through the
labor market
• Less developed markets and risk, risk, risk
Higherriskand
vulnerability
Weakerinstitutions
 With exception of Southern Africa, less fiscal space---
donors play a strong role
 Still missing consensus among national policy makers
 Weak institutional capacity to implement programs
 Weak supply of services (health and education)

7.  Long term effects of improved human capital
o Nutritional and health status; educational attainment
o Labor productivity and employability
 Transfers can relax some of constraints brought on by market failure (lack of
access to credit, insurance)
o Investment in productivity activities
o Improve natural resource management
 Better ability to deal with risks and shocks
o Avoid detrimental risk coping strategies
o Avoid risk averse production strategies
o Increase risk taking into more profitable crops and/or activities
 Transfers can reduce burden on social networks and informal insurance
mechanisms
 Multiplier effects in local village economy
Why do we expect resilience impact?

8. 5+1. Facilitate climate change
adaptation/resilience building
All five pathways related to increasing resilience and
reducing vulnerability at the level of the household,
community and local economy
1. Human capital formation
2. Change/adaptation in productive activities
3. Better ability to deal with risk
4. Reduced pressure on informal insurance networks
5. Strengthened resilience of the local economy
Build household and local level resilience
Research questions
1. Does CT program generate productive impact?
2. Does CT mitigate the negative effect of weather shock?

9. Country Design
Level of Randomization
or Matching
N
Ineligibles
sampled?
Kenya
Social experiment with
PSM and IPW
Location 2234 No
Lesotho Social experiment Electoral District 2150 Yes
Malawi Social experiment Village Cluster 3200 Yes
Zambia Social experiment
Community Welfare
Assistance Committee
2519 No
Ethiopia
Non-experimental (PSM
and IPW)
Household level within a
village
3351 Yes
Ghana
Non-experimental (PSM
and IPW)
Household and Region 1504 No
Evaluation of SCT in SSA - Design
All studies are longitudinal with a baseline and at least one post-intervention follow-up.

10. • Real-world evaluation of government-run cash transfer programs in
seven countries (not rarified experiments)
• Malawi, Ghana, Ethiopia, Lesotho, Zambia and Kenya
• Evidence-based policy support
• Quantitative (emphasis on experimental & econometric methods, randomized
“treatments”)
• Qualitative (perceptions on household economy and decision making, social
networks, local community dynamics & operations)
• Local Economy-wide Impact Evaluation (LEWIE)
• Integrates general-equilibrium and econometric methods
• Data:
• Baseline surveys
• Comparison of treatment & control groups
• Simulations of SCT impacts
• Qualitative methods
• Follow-on surveys
• Estimation of actual SCT impacts
• Validation, updating of simulation models
The Mixed Method Approach
Eligible Ineligible
Eligible Ineligible
TreatmentVillage
ControlVillage

11. What are the key findings?

12. Livelihoods matter for social cash
transfers beneficiaries
• Most beneficiaries in Sub Saharan Africa are rural, engaged in
agriculture and work for themselves
• >80% produce crops; >50% have livestock
• Most grow local staples, traditional technology and low levels of
modern inputs
• Most production consumed on farm
• Most have low levels of productive assets
• few hectares of land, a few animals, basic tools, few years of education
• Engaged on farm, non-farm business, casual wage labour (ganyu)
• Often labour-constrained
• Elderly, single headed household
• Large share of children work on the family farm
• 50% in Zambia, 30% in Lesotho, 42% in Kenya

13. Households invest in livelihood activities—
though impact varies by country
Zambia Malawi Kenya Lesotho Ghana
Agricultural inputs +++ - ++ +++
Agricultural tools +++ +++ NS NS NS
Agricultural production +++ NS ++ NS
Sales +++ NS NS NS - -
Home consumption of
agricultural production
NS +++ +++ NS
Livestock ownership All types All types Small NS NS
Non-farm enterprise +++ NS +FHH
-MHH
- NS
Stronger impact Mixed impact Less impact

14. Improved ability to manage risk
Zambia Kenya Malawi Ghana Lesotho
Negative risk coping - - - - - -
Pay off debt +++ +++ NS
Borrowing - - - NS - - - NS
Purchase on credit NS NS NS
Savings +++ +++ +++ NS
Give informal transfers NS +++ +++
Receive informal transfers NS +++
Remittances - - - NS - - -
Trust (towards leaders)
Strengthened social networks
• In all countries, re-engagement with
social networks of reciprocity—
informal safety net
• Allow households to participate,
to “mingle” again
• Reduction in negative risk
coping strategies
• Increase in savings, paying off
debt and credit worthiness—risk
aversion
• Some instances of crowding out

15. Total
expenditure
Food
expenditure
Non-food
expenditure
Total caloric
intake
Dietary
Diversity
Score
HH received SCT NS NS NS NS ++
(-ve) rainfall shock - - - - - - - - - - - - NS
CGP*rainfall shock
+++ +++ +++ +++ +++
Notes: NS = not significant; + = significant positive impact; – = significant negative impact. One, two or three ‘+’ or
‘–‘ signs refer to significance at, respectively 10, 5 or 1 percent confidence level.
Heterogeneous impact of CT on welfare - GLS-RE
15
Does CT mitigate adverse effect of
weather shock?
Cash transfer mitigate the negative effect
of climate shock

16. a) Daily Caloric Intake b) Food Expenditure
c) Non Food Expenditure
Magnitude of CT effect across quantiles
CT mitigate the negative
effect of climate shock
espcially for the poorest

17. Impact on food security
Ghana Lesotho Kenya Malawi Zambia Ethiopia
Food security +++ +++ N/A +++ +++ +++
Consumption NS + +++ +++ +++ ++
Dietary diversity 0 NS +++ +++ ++ +
Home consumption of crop
production
N/E N/E +++ NS + N/E
Littleimpact Big impact, partially
through increased
agricultural production

18. Crop Livestock NFE Productive labor Social
Network
Zambia yes yes yes yes
Malawi yes yes no yes small
Kenya no small yes yes
Lesotho yes small no no yes
Ghana no no no small yes
WHAT ARE KEY FINDINGS?
18
What explains differences in
household-level impact across
countries?

19. Predictability of payment
Regular and predictable transfers facilitate planning,
consumption smoothing and investment
0
1
Sep-10
Nov-10
Jan-11
Mar-11
May-11
Jul-11
Sep-11
Nov-11
Jan-12
Mar-12
May-12
Jul-12
Sep-12
#ofpayments
Zambia CGP
0
1
2
3
4
5
6
#ofpayments
Ghana LEAP
Regular and predictableLumpy and irregular
19

20. Bigger transfer means more impact
0
5
10
15
20
25
30
35
40
Ghana
LEAP (old)
Kenya CT-
OVC (big)
Burkina Kenya CT-
OVC
RSA CSG Lesotho
CGP (base)
Ghana
LEAP
(current)
Kenya CT-
OVC
(small)
Zim
(HSCT)
Zambia
CGP
Zambia
MCP
Malawi
SCT
Widespread impact
Selective impact
%orpercapitaincomeofpoor
20

21. Demographic profile of beneficiaries
Under 5
5 to 9
10 to 14
15 to 19
20 to 24
25 to 29
30 to 34
35 to 39
40 to 44
45 to 49
50 to 54
55 to 59
60 to 64
65 to 69
70 to 74
75 to 79
80 to 84
85 to 89
Over 90
1000 500 500 1000population
Males Females
Ghana LEAP
Under 5
5 to 9
10 to 14
15 to 19
20 to 24
25 to 29
30 to 34
35 to 39
40 to 44
45 to 49
50 to 54
55 to 59
60 to 64
65 to 69
70 to 74
75 to 79
80 to 84
85 to 89
Over 90
2000 500 500 2000population
Males Females
Zambia CGP
More able-bodiedMore labour-constrained
21

22. Key messages
1. Overall positive effect of the CT on welfare, livelihood
activities and Food security; though heterogenous across
countries
2. CT mitigates against the negative effects of extreme weather
events (negative shocks)…
3. … this effect is higher for lowest quantiles of the distribution.
4. Transfer size, predictability, demographic profile and
complementary intervention is key to maximize the impact

23. Thank you!
sasfaw@gcfund.org
@GCF_Eval