can unconditional cash transfers lead to sustainable poverty reduction?
TRANSCRIPT
unite for children
Can unconditional cash transfers lead to sustainable poverty reduction?
Evidence from two government-led programmes
in Zambia
Sudhanshu Handa, Luisa Natali, David Seidenfeld, Gelson Tembo and Benjamin Davis on behalf of the Zambia CGP Evaluation Team
Presented by Luisa Natali UNICEF Office of Research – Innocenti
September 2016 - University of Florence
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UCTs in sub-Saharan Africa . . .
UCTs: Regular and predictable transfers designed to support poor people. Paid without any behavioural requirement.
Expansion of Cash Transfers: Worldwide: Almost 800 million people enrolled in
SCTs In SSA: in 2014, 40 countries (out of 50) had some
form of UCT in place up from 21 in 2010
Unprecedented accumulated evidence in SSA
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Motivation and study aim
What are the broad impacts of UCTs? Unconditional nature of the CT: hhs free to spend money as
they prefer -> impacts may be found virtually anywhere Most studies report results in one specific topical area Given simplicity and coverage of CTs, argument to use CTs
as benchmark for other poverty interventions
Can UCTs go beyond consumption protection and generate productive impacts? (long-term)
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The Child Grant Programme The Multiple Category Targeting Programme
Started 2010 2011
Eligibility requirements
Households with a child under three enrolled
Female- or elderly-headed household keeping orphans; households with a disabled member; other critically vulnerable cases.
Location3 rural districts of Zambia: Kaputa (Northern Province), Kalabo and Shangombo (Western Province)
2 rural districts of Zambia: Serenje (Central Province) and Luwingu (Northern Province)
Cash transferUS$ 12 per month, flat rate, paid bi-monthlyCT around 25% of pre-program consumption
An amount deemed sufficient to purchase one meal a day for everyone in the household for one month.
Two unconditional cash transfer programs in Zambia
Overall goal: reduce extreme poverty and intergenerational transfer of poverty
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Very similar programs with different demographic profile of households
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Den
sity
0 20 40 60 80 100Age in years
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Den
sity
0 20 40 60 80 100Age in years
CGP MCP
preschoolersadolescents
elderlyprime-age adults
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Zambia implemented ‘gold standard’ evaluations of these two programmes
The Child Grant Programme The Multiple Category Targeting Programme
Design Longitudinal cluster randomized control trial
Sample size 2,519 households 3,078 households
Unit of randomization CWAC - Community Welfare Assistance Committees (90)
CWAC - Community Welfare Assistance Committees (92)
Method of randomization Public lottery Public lottery
CGP MCP
Baseline 2010 2011
Midline (after 24m) 2012 2013
Endline (after 36m) 2013 2014
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Methodology and measures• Impacts on around 40 indicators in 8/9 domains of interest at 24 & 36 months
• Multivariate difference-in-differences model • OLS with robust standard errors clustered at the community level• Full household panel
• All indicators defined so that higher values are positive outcomes and converted into z scores relative to the control group
• 2 approaches to account for multiple testing:• for each family of outcomes, we adjust p-values using the Sidak-Bonferroni
adjustment • we build summary indexes as ‘lead indicators’ for each domain
• Robustness checks: ancova, panel fixed effects, Lee bounds• Sample balanced at baseline, no differential attrition
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DOMAIN Indicators Level
CONSUMPTIONOverall per capita consumption*
HouseholdFood consumptionNon-food consumption
FOOD SECURITY
Does not or rarely worry about food
Household
Able to eat preferred foodDoes not or rarely eat food he/she does not want to due to lack of resources Does not, or rarely, eat smaller meal than needed Does not, or rarely, eat fewer meals because there is not enough food Never or rarely no food to eat because of lack of resourcesDoes not, or rarely, go to sleep hungry Does not, or rarely, go a whole day/night w/o eatingFood security scale (0-24 where higher means more food secure)*
ASSETS Domestic asset index
HouseholdLivestock indexProductive index
FINANCE and DEBT
Whether woman currently saving cashWomanAmount saved by women
Whether household has new loan
HouseholdReduction in the amount borrowedNot having an outstanding longer-term loan (loans taken out more than 6 months before the follow-up considered)Reduction in the amount owed
INCOME and REVENUES Value of harvest ZMW
HouseholdTotal crop expenditures NFEs [operating or not] NFEs [revenues]
RELATIVE (and/or subjective) POVERTY
Not considering household very poorHousehold
Better off compared to 12 months agoThink life will be better than now in either 1, 3 or 5 years Woman
MATERIAL NEEDSShoes
Child (5-17)BlanketTwo sets of clothesAll needs met*
SCHOOLING School enrolment Child (11-17)Days attended in prior week
NUTRITION OF YOUNG CHILDREN [CGP only]
Not underweightChild (0-5)Not wasted
Not stunted
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Results…
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Effects of CGP on consumption
ITT in actual units
Food consumption
Non-food consumption
Total consumption1
Impact at 24 months 0.28*** 0.23*** 0.28***
(0.07) (0.07) (0.07)
Impact at 36 months 0.19*** 0.19** 0.20***
(0.05) (0.07) (0.05)
R2 0.25 0.19 0.27
N 6,813 6,813 6,813
Mean standardized ITT
Food consumption
Non-food consumption
Total consumption1
Impact at 24 months 0.47*** 0.37*** 0.48***
(0.10) (0.10) (0.10)
Impact at 36 months 0.34*** 0.35*** 0.38***
(0.07) (0.12) (0.07)
R2 0.2 0.17 0.23
N 6,813 6,813 6,813
Notes: Estimations use difference-in-difference modelling. Robust standard errors clustered at the community level are in parentheses. * p<0.1 ** p<0.05; *** p<0.01. Estimations are adjusted and include recipient’s age, education and marital status, household size and household demographic composition, and districts.
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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 of the control group
36-month results at a glanceImpacts from both programs similarMCP
CGP
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Total consumption pc*Food consumption pcNon-food consumption pc
Does not worry about foodDoes not go to sleep hungry at nightDoes not go whole day w/o eating
Domestic asset indexLivestock indexProductive asset index
Harvest value [ZMW]Agricultural input spending [ZMW]Operating a NFERevenues from NFEs
Held any savings (women only)Amount saved [ZMW] (women only) No outstanding debtReduction in amount owedNo new borrowingReduction in amount borrowed
Does not consider hh very poorHh better off compared to 12 months agoLife will be better in the future (women only)
ShoesTwo sets of clothesBlanket
Currently enrolledDays in attendance prior week
Not stuntedNot wastedNot underweight
Consumption
Food security
Assets
Income and Revenues
Finance and Debt
Relative Poverty
Material needs (children 5-17)
Schooling (children 11-17)
Nutrition (Young children 0-59m)
-.2 0 .2 .4 .6 .8 1 1.2 1.4 1.6
CGP (Child Grant) impacts at 36 months
Effect size in SDs of the control group
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Total consumption pc*Food consumption pcNon-food consumption pc
Does not worry about foodDoes not go to sleep hungry at nightDoes not go whole day w/o eating
Domestic asset indexLivestock indexProductive asset index
Harvest value [ZMW]Agricultural input spending [ZMW]Operating a NFERevenues from NFEs
Held any savings (women only)Amount saved [ZMW] (women only) No outstanding debtReduction in amount owedNo new borrowingReduction in amount borrowed
Does not consider hh very poorHh better off compared to 12 months agoLife will be better in the future (women only)
ShoesTwo sets of clothesBlanket
Currently attendingDays in attendance prior week
Consumption
Food security
Assets
Income and Revenues
Finance and Debt
Relative Poverty
Material needs (children 5-17)
Schooling (children 11-17)
-.2 0 .2 .4 .6 .8 1 1.2 1.4 1.6
MCP impacts at 36 months
Effect size in SDs of the control group
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CGP MCP On average
Multiplier effect 1.46 1.72 1.59
Both programmes leverage more money than value of transfer received
Impacts are based on estimated econometric results and averaged across all follow-up surveys. Only statistically significant (at the 5 per cent level) impact estimates are considered. Loan repayments were not measured in the CGP at 24 months.
Household level multiplier =
On average, beneficiary hhs convert each Zambian kwacha of tranfer into an additional 0.59 ZMW worth of income
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Conclusions• Same overall transformative effects across two programs• Effect not just on primary objective (protective) but also on a range of
productive and economic outcomes -> potential for sustained pathway out of poverty?
• Impacts do not differ significantly across hh eligibility type [external validity]• No impact on anthropometric indicators in CGP• Beneficiaries households spend (59%) more money than value of
transfer itself
• From research to policy: • Impact evaluation evidence played key role in policy changes (scale-up
decisions and budget allocations)• Contributes to cross-country learning under the Transfer Project
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• Transfer Project website: www.cpc.unc.edu/projects/transfer • Briefs: http://
www.cpc.unc.edu/projects/transfer/publications/briefs
• Facebook: https://www.facebook.com/TransferProject • Twitter: @TransferProjct Email: [email protected]
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Ghana, credit: Ivan Griffi