Transcript Social cash transfer programs in Sub

Productive Impacts of Social Cash
Transfer Programs in Sub-Saharan
Africa.
Solomon Asfaw et al.
FAO of the United Nations, Rome, Italy
the From Protection to Production Project
Dakar, Senegal
26 November 2015
Social cash transfer programs in
Sub-Saharan Africa
• Target households that are poor and vulnerable, with few assets
and often limited labor—the poorest of the poor
• Eligibility often includes presence of orphans and vulnerable
children
• Many elderly or single-headed households, which face
constraints in caring for children
• Usually unconditional
– …though sometimes some “messaging,” e.g., about using the cash for
children
• Objectives focus on reducing poverty and vulnerability, assuring
food security, protecting children
• Most beneficiaries in SSA are rural, engaged in agriculture and
work for themselves
Theory of SCT Impacts
(Always Entail Market Failures)
• Long term effects of improved human capital
– Nutritional and health status; educational attainment
– Labor productivity and employability
• Transfers can relax some of constraints brought on
by market failure (lack of access to credit, insurance)
– Helping households manage risk
– Providing households with liquidity
• Transfers can reduce burden on social networks and
informal insurance mechanisms
• Infusion of cash can lead to multiplier effects in local
village economy
Mixed Method Approach
• Real-world evaluation of government-run cash transfer programs in
seven countries (not rarified experiments)
• 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)
•
• Data:
Integrates general-equilibrium and econometric methods
– Baseline surveys
•
•
Comparison of treatment & control groups
Simulations of SCT impacts
– Qualitative methods
– Follow-on surveys
•
•
Treatment Village
Estimation of actual SCT impacts
Validation, updating of simulation models
Eligible Ineligible
Control Village
– Link to historical rainfall data – Zambia CGP
Eligible Ineligible
Core Evaluation Designs
Level of
Randomization or
Matching
Ineligibles
sampled?
Country
Design
Kenya
Social experiment with
Location
PSM and IPW
No
Lesotho
Social experiment
Electoral District
Yes
Malawi
Social experiment
Village Cluster
Yes
Zambia
Social experiment
Community Welfare
No
Assistance Committee
Ethiopia
Non-experimental
(PSM and IPW)
Household level within
Yes
a village
Ghana
Propensity Score
Matching (IPW)
Household and Region No
All studies are longitudinal with a baseline and at least one post-intervention
follow-up.
Results so far
Households invest in livelihood activities—
though impact varies by country
Zambia
Malawi
Kenya
Lesotho
+++
++
-
++
-I.seed,
+fert
+++
Agricultural tools
+++
++
NS
NS
Mixed
NS
Agricultural production
+++
+
NS
++(3)
++
NS
Sales
+++
NS
NS
NS
Mixed
--
Home consumption of
agricultural production
NS
NS
+++
All types
All types
Small
Pigs
-
NS
+++
NS
+FHH
-MHH
-
NS
NS
Agricultural inputs
Livestock ownership
Non farm enterprise
Stronger impact
Ethiopia Ghana
NS
Mixed impact
Less impact
Shift from casual wage labor to on farm
and family productive activities
adults
Ghana
Agricultural/casual wage
labor
---
--(1,2)
---
- - (2)
NS
Family farm
+ (2)
++ (1)
++
++ (2)
+++
Non farm business
+++
NS
NS
+
NS
+++
NS
+men,
-women
NS
NS
NS
Wage labor
NS
NS
+
NS
-
NS
Family farm
NS
- - - (3)
- (4)
--
--
NS
Non agricultural wage
labor
children
1)
2)
3)
4)
Zambia Kenya Malawi Lesotho Ethiopia
Positive farther away
No clear picture on child labor (but
Varies by age, gender
positive impacts on schooling)
Particularly older boys
Shift from casual wage labour to
Mixed chores, reduction in ganyu
family business—consistently
reported in qualitative fieldwork
Zambia—continuous treatment effect model:
how impact changes with level of cash transfer
Labor supply
As transfer level
increases, greater
reduction in wage labor
and greater increase in
own farm labor
Non labor income
Any Wage Labor;
Non labor income
Own farm labor
Labor supply
Derived by numerical integration
As transfer level
increases, greater
increase in hired labor
Improved ability to manage risk
Zambia Kenya
Negative risk coping
Malawi
Ghana Lesotho
---
Pay off debt
+++
Borrowing
---
Purchase on credit
NS
Savings
+++
++
NS
---
NS
NS
NS
+++
NS
NS
+++
+++
NS (1)
-
NS
+++
NS (1)
NS
---
-+++
Receive informal transfers
Remittances
--
+++
NS
Give informal transfers
---
Ethiopia
+
1) More support to poor and fewer problems with neighbours in community, life satisfaction
• Reduction in negative risk
coping strategies
• Increase in savings, paying
off debt and credit
worthiness—risk aversion
• Some instances of crowding
out
Strengthened social networks
• In all countries, re-engagement with
social networks of reciprocity—
informal safety net
• Allow households to participate,
to “mingle” again
Broad range of impacts
(though variation across countries)
• Beneficiaries are happier and more confidant
– People with hope more likely to invest in future
• Increased food security (access and quality)
• Improvement in different aspects of child welfare
– Increased school enrolment
– Reduction in morbidity (diarrhea/illness)
– Increased access to shoes, clothing, birth registration,
vaccination
• Safe-transition of adolescents into adulthood
– Reduction in transactional sex, sexual debut, pregnancy
What explains differences in household-level
impact across countries?
Crop
Livestock
NFE
Productive
labor
Zambia
yes
yes
yes
yes
Kenya
no
small
no
yes
Malawi
small
yes
no
small
Lesotho
yes
small
no
no
Ethiopia
small
no
no
no
no
no
Ghana
Social
Network
yes
yes
small
yes
Predictability of payment
Regular and predictable
Lumpy and irregular
Zambia CGP
Ghana LEAP
6
1
4
3
2
# of payments
# of payments
5
1
0
0
Regular and predictable transfers facilitate planning,
consumption smoothing and investment
Bigger transfer means more impact
% or per capita income of poor
40
Widespread impact
35
30
Selective impact
25
20
15
10
5
0
Ghana
LEAP
(old)
Kenya Burkina Kenya
CT-OVC
CT-OVC
(big)
RSA
CSG
Lesotho Ghana
Kenya
Zim
CGP
LEAP CT-OVC (HSCT)
(base) (current) (small)
Zambia
CGP
Zambia
MCP
Malawi
SCT
Demographic profile of beneficiaries
More labour-constrained
More able-bodied
Ghana LEAP
1000
500
Over 90
Over 90
85 to 89
85 to 89
80 to 84
80 to 84
75 to 79
75 to 79
70 to 74
70 to 74
65 to 69
65 to 69
60 to 64
60 to 64
55 to 59
55 to 59
50 to 54
50 to 54
45 to 49
45 to 49
40 to 44
40 to 44
35 to 39
35 to 39
30 to 34
30 to 34
25 to 29
25 to 29
20 to 24
20 to 24
15 to 19
15 to 19
10 to 14
10 to 14
5 to 9
5 to 9
Under 5
Under 5
population
Males
Zambia CGP
500
Females
1000
2000
population
500
500
Males
2000
Females
Impacts beyond the beneficiary household:
local economy income multipliers
• Transfer raises purchasing power of beneficiary households
• As cash spent, impacts spread to others inside and outside treated
villages, setting in motion income multipliers
• Purchases outside village shift income effects to non-treated
villages, potentially unleashing income multipliers there.
• As program scaled up, transfers has direct and indirect (general
equilibrium) effects throughout region.
• Three possible extremes:
– Local supply expands to meet all this demand
•
Big local multiplier
– Everything comes from outside the local economy
•
No local multiplier at all: 1:1
– Local supply unable to expand to meet demand, and no imports
•
Inflation
• Have to follow the money
– Surveys and LEWIE model designed to do this
Simulated income multiplier
of the Ghana LEAP programme
MAX
Every 1 Cedi transferred can
generate 2.50 Cedi of income
Base model
Income multiplier
Nominal
(CI)
2.50
(2.38 – 2.65)
Real
(CI)
1.50
(1.40 – 1.59)
Source: Thome et al., 2014
Production constraints can
limit local supply response,
which may lead to higher
prices and a lower multiplier
When constraints are
binding, every 1 Cedi
transferred can generate 1.50
Cedi of income
MIN
Cash transfers lead to income multipliers
across the region
Every 1 Birr transferred can
generate 2.52 Birr of income
3
2.5
Income multiplier is greater
than 1 in every country
If constraints are
binding, may be
as low as 1.84
2
1.5
1
0.5
0
Kenya
(Nyanza)
Ethiopia (AbiAdi)
Zimbabwe
Zambia
Nominal multiplier
Kenya
(Garissa)
Real multiplier
Lesotho
Ghana
Ethiopia
(Hintalo)
Beneficiaries are hard working and are responsible
for their own income generation and food security
How can cash transfers be better linked to
livelihoods? Implications support to small holders?
1. Ensure regular and predictable payments
2. Link cash transfers to livelihood interventions
3. Consider messaging—it’s ok to spend on economic
activities
4. Consider expanding targeting to include households with
higher potential to sustainably achieve self-reliance
–
including able-bodied labour
But keeping in mind potential conflicts and synergies
with social objectives
Reference
1. Asfaw, S., Davis, B., Dewbre, J., Handa, S. and Winters, P. (2014). Cash transfer
programme, productive activities and labour supply: Evidence from randomized
experiment in Kenya. Journal of Development Studies, 50(8):1172-1196.
2. Asfaw, S., Carraro, A., Pickmans, R., Daidone. S. & Davis, B. (2015b). Productive Impacts
of the Malawi Social Cash Transfer Programme. PtoP project report, forthcoming, FAO,
Rome.
3. Asfaw, S., Pickmans, R., Alfani, F. and Davis, B. (2015a). Productive Impact of Ethiopia’s
Social Cash Transfer Pilot Programme, PtoP project report, FAO, Rome
4. Daidone, S., Davis, B., Dewbre, J. & Covarrubias, K., (2014a). Lesotho Child Grants
Programme: 24-month impact report on productive activities and labour allocation
PtoP project report, FAO, Rome
5. Daidone, S., Davis, B., Dewbre, J., Gonzalez-Flores, M., Handa, S., Seidenfeld, D. &
Tembo, G.,( 2014b). Zambia’s Child Grant Programme: 24-month impact report on
productive activities and labour allocation PtoP Project Report, FAO, Rome.
6. Thome, K., Taylor, JE., Kagin, J., Davis, B., Darko Osei, R., Osei-Akoto, I. & Handa, S.
(2014b). Local Economy-wide Impact Evaluation (LEWIE) of Ghana’s Livelihood
Empowerment Against Poverty (LEAP) program, PtoP project report, FAO and The
World Bank.
7. Taylor, JE., Kagin, J., Filipski, M., Thome, K & Handa, S., (2013a). Evaluating general
equilibrium impacts of Kenya's Cash Transfer Programme for Orphans and Vulnerable
Children PtoP project report, FAO and The World bank.
Our websites
From Protection to Production Project
www.fao.org/economic/PtoP
The Transfer Project
www.cpc.unc.edu/projects/transfer