1. The Impact of Cash Transfer Programs in sub- Saharan Africa: Evidence from the Transfer Project Sudhanshu Handa UNICEF Office of Research-Innocenti https://transfer.cpc.unc.edu/ Outline 1.Overview on development oriented cash transfers in SSA 2.Summary of impacts – claims and ‘myth busters’ 3.The future agenda for programming and research

2. Social Protection is thriving in Africa Focusing on cash transfer programs alone – >120 programs across the continent of all kinds (Garcia & Moore 2012) – ~30 long-term development programs in 20 countries Programs are ‘home-grown’ – Target on poverty and vulnerability; greater role of community – Unconditional or ‘soft conditions’ – Larger evidence base on impacts than any other region: more countries, more topics

3. Cash Transfer Programs in Sub-Saharan Africa: The ‘quiet’ revolution 3 No CTs After 2004 Prior to 2004 No data

4. Households covered in selected programs (RSA excluded; ETH direct beneficiaries only) Rapid scale-up in last year

5. Transfer Project: Regional initiative to study impact of CTs in SSA Led by UNICEF with partner governments – FAO on productive impacts and local economy Rigorous evaluations of national programs – Technical support, design, analysis, policy dialogue SSA now has largest evidence base on cash transfers anywhere in the world – Over a dozen rigorous evaluations – In SSA, we no longer need to refer to the “Latin American evidence on CCTs”

6. Malawi SCT Zimbabwe HSCT Unique demographic structure of recipient households in OVC and labor-constrained models (missing prime-ages)

7. Labor-constrained criterion selects unique households: Zambia Zambia SCT HouseholdsRural Ultra-Poor LCMS 2010

8. Kalabo Districts – 12+ hours by car from Lusaka Suspicious characters Kaputa District – 20+ hours by car from Lusaka

9. Beneficiary, Migori District, Kenya (missing generation family) Beneficiary, Serenje District, Zambia (missing generation family) (household’s water source)

10. How much do programs pay? Benefit structure and level in selected programs (US$) # membersGhana LEAP Malawi SCT MOZ PSA Zimbabwe HSCT Kenya CT- OVC Zambia SCT 1 person82.8371015 flat12 flat 29.503.66915 3114.831120 4+13.256.1713.5025 Beneficiary consumption pp per day 0.620.340.500.850.700.30 ZAM: $24 if disabled member MLW: 0.83 and 1.67 top-up per child in primary and secondary school respectively

11. Among other things, impact depends on transfer size Widespread impact Selective impact % or per capita consumption

12. Claim: Cash is ‘wasted’ on alcohol and tobacco Alcohol & tobacco represent 1 percent of budget share Across seven countries, no positive impacts observed on alcohol and tobacco – Data comes from detailed consumption modules covering over 250 individual items Alternative measurement approaches yield same result – “Has alcohol consumption increased in this community over the last year?”

13. Big impacts on food security, consumption or diet diversity Ghana*10pp reduction in proportion of children missing a meal for an entire day Ethiopia12% increase in diet diversity; 150 calories per week increase in food (6%) Lesotho11pp reduction in proportion of children who had to eat fewer meals because of food shortage; reduction by 1.5 in number of months hhld had extreme shortage of food Malawi30% increase in consumption; 60pp increase in proportion of households eating meat or fish (diet diversity) Kenya10% increase in consumption (and improved diet diversity) Zambia CGP30% increase in consumption (and improved diet diversity) Zimbabwe8% increase in consumption; 10% increase in diet diversity

14. Claim: Cash not used for productive activity or investment, just a ‘hand-out’

15. School enrollment impacts among secondary age children strong, equal to those from CCTs in Latin America All Girls only Primary enrollment already high, impacts at secondary level

16. Grade 3 math test – Serenje District, Zambia

17. Households invest in productive activities: impact varies by country, transfer size, target group ZambiaEthiopiaMalawiZimLesothoKenyaGhana Agricultural inputs+++ NS++NS+++ Agricultural tools+++ NS Agricultural production +++ NS ++NS Livestock ownership+++ ++SmallNS Non farm enterprise+++NS +++NS+FHHNS Stronger impact Mixed impact Less impact NS=not significant

18. Claim: Leads to laziness “I used to be a slave to ganyu (labour) but now I’m a bit free.” -elderly beneficiary, Malawi

19. Reduction in casual wage labor, shift to on farm and more productive activities adultsZambiaKenyaMalawiEthiopiaZIMLesothoGhana Agricultural/casual wage labor - - - --NS Family farm+++ NS+++NS +++ Non farm business (NFE)+++ NS Non agricultural wage labor +++NS+++NS Shift from casual wage labour to family business— consistently reported in qualitative fieldwork

20. Claim: Cannot be scaled up—not affordable Plausible simulations show average cost 1.1% of GDP or 4.4% of spending

21. Claim: Lead to inflation In six countries, tested for inflation in intervention versus control communities using basket of ten goods – No inflationary effects found Why not? – Beneficiaries small share of community, typically 15-20 percent – Poorest households, low purchasing power, don’t buy enough to affect market prices

22. In fact, cash transfers lead to multiplier effects in local economy!!

23. Can it really be this good? Impacts on health inconsistent – Health expenditures increase, some increase in curative care, no consistent effects on illness No impacts on child nutritional status – In RSA, Zambia, positive impacts when mother has completed primary school – Determinants of nutrition complex, involve care, sanitation, water, disease environment and food – Weak health infrastructure in deep rural areas

24. -13 pp impact***  Kenya and Zimbabwe impacts driven by girls, Malawi driven by boys. Zambia no impacts! -11 pp impact*** Meanwhile, emerging evidence that transfers enable safe-transition of adolescents into adulthood: Impacts on sexual debut among youth

25. And beneficiaries are happier too-- consistent impacts on subjective well-being Ghana LEAP16pp increase in proportion reporting ‘yes’ to “Are you happy with your life?” Malawi SCT20pp increase in proportion ‘very satisfied’ with their life Kenya CT-OVC*6% increase in Quality of Life score Zambia CGP45% increase in proportion who believe ‘they are better off than 12 months ago’ Zambia Monze*10pp increase in proportion who feel ‘their life will be better in 2 years” Zimbabwe12% increase in subjective well-being scale

26. What is on the future agenda? How can Sida help? Programming – Explicit links with social services (health insurance, school fee waivers) and where appropriate, agricultural and business services – Building comprehensive social protection system with cash transfers as the core – Policy and operational integration (MIS, targeting…) – Keep peddling or else you fall off

27. What is on the future agenda? How can Sida help? Research and Evidence – Do we need yet another impact evaluation? Each country wants to know if it works in their context Well designed set of studies inform program design and operations – Rigorous research sends strong signal of professionalism – Keep peddling… The LAC model continues to dominate the discourse in certain places African model and evidence still not mainstreamed

28. The (Innocenti) Transfer Project Team Amber Peterman [Gender/youth] Jacob de Hoop [Education/child labor] Sudhanshu (Ashu) Handa [Basically everything] Lisa Hjelm [Food security/ poverty & stress] Tia Palermo [Gender/youth] Michelle Mills [Research dissemination] Luisa Natali [Zambia/labor] Leah Principe [Zambia/ECD] Audrey Pereira [violence/ maternal health] Richard de Groot [Education & nutrition/Ghana] ** Missing in action: Frank Otchere [Resilience/poverty]