impacts of cash transfers on schooling
TRANSCRIPT
Heterogeneous Impacts of an Unconditional Cash Transfer Programme on Schooling: Evidence from the Ghana LEAP Programme
Richard de Groota, Sudhanshu Handaa, Michael Parkb, Robert Osei Darkoc, Isaac Osei-Akotoc, Garima Bhallab, Luigi Peter Ragnod
a UNICEF Office of Research – Innocentib University of North Carolina at Chapel Hill, Department of Public Policy
c Institute of Statistical, Social and Economic Research, University of Ghana – Legond UNICEF Ghana Country Office
Adolescence, Youth and Gender: Building Knowledge for Change ConferenceOxford, September 8, 2016
Introduction Findings from Ghana Livelihood Against
Poverty (LEAP) programme What is the effect of an unconditional
cash transfer programme on schooling outcomes for children?
Do parents display compensating or reinforcing behaviour towards lower ability children (‘marginal’ child)?
Is there a need for conditionality in this case? (i.e. strict rules attached to receipt of transfer)
Ghana LEAP programme Ghana’s flagship social protection programme Initiated in 2008, currently reaching
>150,000 households (and counting!) Cash payments and health insurance Three demographic groups:
Orphaned and vulnerable children (OVC’s), elderly and people with a disability (PWD)
Soft conditions for OVC households Transfer level: 7% of household consumption
Methods Core: Difference-in-Difference (DD) with
Propensity Score Matching (PSM) Treatment group (N=699) pulled from
2010 extension in 3 regions (Brong Ahafo, Central & Volta)
Comparison group (N=914) pulled from national survey
Identical survey instruments, teams and field work methods Ideal conditions for PSM!
Methods Inverse Probability Weighting (IPW)
IPW uses inverse of the propensity score: Higher score, more similar to LEAP
household Covariate adjustment Cluster fixed effects Sample size (children 5 – 17 years):
Comparison TreatmentBaseline (2010)
1,239 979
Follow-up (2012)
1,076 869
Methods Schooling indicators:
Current enrolment Attendance (missed any school in last 7
days) Analyze effect by subgroups:
Age group (5 – 12 and 13 – 17) Sex Cognitive ability (Raven’s test)
Ghana LEAP - Impacts on school enrollment
Impacts on enrollment large for older boys
All c
hild
ren
5 - 1
7 ye
ars
All
Boy
s
Gir
ls All
Boy
s
Gir
ls
Children 5 - 12 years Children 13 - 17 years
-100
1020
-0.7
-4.9**
1.1
8.1**
20.3***
1.3
0.4
Ghana LEAP - Impacts on any missed school
Impacts on attendance for younger children and older girls
All c
hild
ren
5 - 1
7 ye
ars
All
Boy
s
Gir
ls All
Boy
s
Gir
ls
Children 5 - 12 years Children 13 - 17 years
-14-10
-6-22
-8.5***-10.5***
-13.0***-8.3**
-5.4 0.4
-9.8*
Impacts on school enrollment by cognitive ability
Higher impact among older children with low cognitive ability (the ‘marginal’ child)
All children 5 - 17 years
Children 5 - 12 years
Children 13 - 17 years
Boys 5 - 17 years
Girls 5 - 17 years
-10-505
10152025
Low cognitive ability
-6.4**
22.0***
4.1*8.5*
5.4*
Impacts on any missed school by cognitive ability
Strong impact observed among children with low cognitive ability compensating behavior of parents
All children 5 - 17 years
Children 5 - 12 years
Children 13 - 17 years
Boys 5 - 17 years
Girls 5 - 17 years
-14-12-10-8-6-4-202
Low cognitive ability
-8.7**-12.8*** -12.8**
Pathways of impact How did LEAP create an increase in
enrolment and attendance? Analyze effects on schooling inputs:
Significant increases in schooling expenditures (books, uniforms, total schooling expenditures)
LEAP may have loosened constraints on out-of-pocket educational expenditures
Conclusion Ghana LEAP showed strong impacts on
children’s schooling Important to move beyond average
treatment effects Strong impacts on adolescent boys
positive elasticity of demand for schooling
Significant increase in enrolment for older children with low cognitive ability
Suggests that parents demonstrate compensating behavior towards their children, if given the chance
School enrollment impacts among secondary age children strong, equal to those from CCTs in Latin America
Malawi S
CTP
Lesoth
o
Ghana
LEAP
Kenya
CT-O
VC
South
Afri
ca C
GP
Zambia
MCP
Mexico
Opo
rtunid
ades
Colombia
FA
Ecuad
or B
DH048
121620
Notes: Bars represent percentage point impacts. Enrollment for primary aged children already high, thus impacts reported at secondary age enrollment
Cross-country impacts on secondary age school enrollment (percentage point impacts similar or above Latin American
CCTs)
Zimbabwe: No impacts on enrollment (crowding out due to Basic Education Assistance Module - BEAM). However, 7 pp increase in attendance.