Ashua Handa (UNC) presented long-term evidence of the impact of cash transfers in Zambia at Oxford’s Center for the Study of African Economies Conference in March 2019.

1. In search of the holy grail: Can
unconditional cash transfers graduate
households out of poverty?
Sudhanshu Handa & Gustavo Angeles - UNC
Gelson Tembo – UNZA and Palm Associates
Luisa Natali - UNICEF Office of Research

2. Exploit reform of cash transfer system to see what
happened to households who were removed
• From 2004-2014 Zambian government experimented with different
cash transfer models
• Two new models introduced in 2010 and 2011, accompanied by RCTs
• Child Grant Program (CGP): evaluation period 2010-2014
• Multiple Category Grant: evaluation period 2011-2014
• In 2014 policy decision to merge all programs into one social cash
transfer program (SCT), scale-up began in 2015, case load now 550k
• What happened to those not eligible for the new program?

3. An exciting period in Zambia for cash transfers
GoZ budget contribution went from $5m to $35m in 2014 and $45m in 2015
0
50000
100000
150000
200000
250000
2003 2005 2007 2009 2011 2013 2015 2017
Households Reached by Cash Transfers in Zambia
CGP MCP
follow-ups
CGP MCP
baselines
CGP MCP
follow-ups
GoZ take over
Election

4. 4

5. 2,519 households
February 2011
Treatment arm Control arm
1,153 households 1,145 households
1,221 households 1,179 households
1,221 households 1,238 households
1,197 households 1,226 households
1051 households 1087 households
September-October 2014 48-month follow-up
September-October 2017 84-month follow-up
October-November 2010: Baseline survey
First transfer in treatment communities
October-November 2012: 24-month follow-up
June-July 2013: 30-month follow-up
October-November 2013: 36-month follow-up
797 out
(75%)
841 out
(77%)
CGP Impact Evaluation

6. 6
Total consumption pc [24m]
[36m]
Food security scale (HFIAS) [24m]
[36m]
Overall asset index [24m]
[36m]
Relative poverty index [24m]
[36m]
Incomes & Revenues index (SD) [24m]
[36m]
Finance & Debt index (SD) [24m]
[36m]
Material needs index (5-17)[24m]
[36m]
Schooling index (11-17) [24m]
[36m]
Anthropometric index (11-17) [24m]
[36m]
-.2 0 .2 .4 .6 .8
Effect size in SDs of the control group
Endlines 1&2 (24&36-months) at a glance
Intent-to-Treat effects (CGP) - indices
Large effects at 36m on
productive and protective
Domains
Big implied multiplier
JDE Vol. 133 (2018)

7. Follow-up study details
• Went back to CGP households in 2017 (Kalabo, Shangombo, Kaputa)
•
• Kaputa: Retargeting implemented in 2015 in study sites
• Shangombo & Kalabo: implemented in 2017 in study sites
• But households were also being graduated due to age of child!
• Mean months of exposure is 45 (Jan 2011 – Sep 2014)
• Control households who were ineligible for SCT received ZM500

8. -Mean exposure 45 months
-Last group were paid in Q1
of 2017
-Survey done Q4 2017

9. Retargeting and thus exposure
varied across districts

10. Research questions
• What happened to households who stopped receiving cash?
• Compare original CGP households who were ineligible vs original control
households who were also ineligible
• What happened to original controls who became eligible?
• Compare them to original treatment households who remained eligible
• How does this inform broader ‘graduation from poverty’ debate?
• Are initial impacts sustained by everyone? Are there high fliers who can help
us understand graduation from poverty?

11. 11
Total consumption pc
Food security scale
Overall asset index
Relative poverty index
Incomes & Revenues index (SD)
Finance & Debt index (SD)
Material needs index (5-17)
Schooling index (11-17)
-.2 0 .2 .4 .6 .8
Effect size in SDs of the control group
At 36- and 84-months
Intent-to-Treat effects (CGP Ineligibles)36m
84m
What happened to households who
were no longer eligible?
Differences no longer significant
These are the purple effect sizes and
Cis, all include 0

12. What happened to those who were removed from
the CGP? Consumption, food security

13. What happened to those who were removed from
the CGP? Subjective well-being

14. What happened to those who were removed from
the CGP? Productive and economic indicators

15. Conclusions on what happened to those who
were removed from the cash transfer?
• Gradual convergence on protective outcomes, not a steep drop
• Slight decline in original T, and slight increase in C
• Remember C also received ZM500 lump-sum, which could explain their
gradual increase
• Convergence slower for productive indicators
• Assets, agricultural input spending, area cultivated
• Results not sensitive when accounting for length of exposure
• Length of exposure and separating out Kaputa

16. How about new recipients—did they catch-up
immediately? Yes! All 84m effects include 0

17. Comparing new SCT recipients with eligible CGP households:
Complete catch-up

18. Do new recipients catch-up? Productive indicators

19. Search for the Holy Grail…
• Are there some households that maintained their consumption after
leaving the program? HIGH FLYERS
• Who are they? What did they do? What secrets do they hold about
‘graduating’ out of poverty?
• How do we define a HIGH FLYER? (Work in progress)
• Two examples

20. Among Original T ineligibles, identify consumption
trajectory suggesting ‘high flyer’

21. The Holy Grail

22. Any individual features that distinguish high flyers?
High Fliers Others
Household size 5.7 5.7
# of able-bodied members 1.93 1.90
Highest grade of CGP recipient 6 4
Individual FISP receipt 2.50 1.75
Distance to nearest market (km) 2.3 2.7
Impatient (never wait for future money) (%) 11 16
Life will be better in 3 years (%) 72 62

23. Livelihood diversification?

24. Any community level factors to explain the high fliers?
0
10
20
30
40
50
60
70
FISP Seed Support Ag Extension Microfinance Skills Training Kalabo
Community features (%)
High Flyer Other

25. Another definition of HIGH FLYER: Top quartile of
consumption distribution at 36m and 84m (~10% of
households fall in this category)
High Fliers Others
Household size 4.9 5.8
# of able-bodied members 1.8 1.9
Highest grade of CGP recipient 6 4
Individual FISP receipt 2.2 2.0
Distance to nearest market (km) 2.4 2.4
Impatient (never wait for future money) (%) 16 16
Life will be better in 3 years (%) 68 62

26. Livelihooddiversificationstorynolongerholds

27. Any community level factors to explain the high fliers?
0
10
20
30
40
50
60
70
FISP Seed Support Ag Extension Microfinance Skills Training Kalabo
Community features (%)
High Flyer Other

28. The search continues….

29. Preliminary conclusions and next steps
• What happens to those who left program?
• Gradual convergence with original C group, slower for assets/productive
• New entrants to SCT converge quickly to long-time recipients
• Households are ultra-poor, transfer size is ~15% of consumption
• Search for the Holy Grail
• Use machine learning, group-based trajectory model, other definitions
• See if patterns emerge on who they are, what they did, context
• High flyers in the original control group too!?!