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Impact of Cash Transfer Programs in Building Resilience: Insight from African Countries

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Impact of Cash Transfer Programs in Building Resilience: Insight from African Countries

  1. 1. Impact of CashTransfer Programs in Building Resilience: Insight from African Countries Independent Evaluation Unit (IEU) Green Climate Fund (GCF) October 26, 2018, South Korea Solomon Asfaw, PhD Principal Evaluation Officer
  2. 2. Outline 1. Background of CT in SSA 2. Why do we expect resilience impact? 3. What does the evidence say? 4. Final remark
  3. 3. Preview: Risk matters Production risk Price risk  Climate,  Pests,  Fire, etc.  Imported price volatility  Natural price volatility  Endogenous price volatility HR risks Regulation risks Financial risks Revenue instability  Reduction of investment within food production in composition and volume  Reduction of consumption and investment in other non-food activities of households  Access to credit  Credit costs  Change in policies/norms (health, environment, etc.)  Diseases / disabilities 3
  4. 4. How to manage risks and food insecurity?  Activities designed to reduce the likelihood of an adverse event or reduce the severity of actual losses (e.g. Irrigation, use of resistant seeds; improved early warning system; adoption of better agronomic practices etc.) MITIGATE TRANSFER COPE 1 2 3  This entails the transfer of risk to a willing party, for a fee or premium. (e.g. Commercial insurance and hedging etc.)  This involves improving resilience to withstand and cope with events (e.g. social safety nets, buffer funds, savings, strategic reserves etc.) 4
  5. 5.  Approximately half of the countries of SSA have some kind of government-run CT program • And others have multilateral/NGO-run CT programs  Some programs are national • Others scaling up • Some pilots beginning this year  Beneficiaries predominately rural, most engaged in agriculture Expansion of cash transfer programs in Sub-Saharan Africa
  6. 6. What’s particular about cash transfers in SSA--context  HIV/AIDS • Economic and social vulnerability  Widespread poverty  Continued reliance on subsistence agriculture and informal economy • Exit path from poverty is not necessarily through the labor market • Less developed markets and risk, risk, risk Higherriskand vulnerability Weakerinstitutions  With exception of Southern Africa, less fiscal space--- donors play a strong role  Still missing consensus among national policy makers  Weak institutional capacity to implement programs  Weak supply of services (health and education)
  7. 7.  Long term effects of improved human capital o Nutritional and health status; educational attainment o Labor productivity and employability  Transfers can relax some of constraints brought on by market failure (lack of access to credit, insurance) o Investment in productivity activities o Improve natural resource management  Better ability to deal with risks and shocks o Avoid detrimental risk coping strategies o Avoid risk averse production strategies o Increase risk taking into more profitable crops and/or activities  Transfers can reduce burden on social networks and informal insurance mechanisms  Multiplier effects in local village economy Why do we expect resilience impact?
  8. 8. 5+1. Facilitate climate change adaptation/resilience building All five pathways related to increasing resilience and reducing vulnerability at the level of the household, community and local economy 1. Human capital formation 2. Change/adaptation in productive activities 3. Better ability to deal with risk 4. Reduced pressure on informal insurance networks 5. Strengthened resilience of the local economy Build household and local level resilience Research questions 1. Does CT program generate productive impact? 2. Does CT mitigate the negative effect of weather shock?
  9. 9. Country Design Level of Randomization or Matching N Ineligibles sampled? Kenya Social experiment with PSM and IPW Location 2234 No Lesotho Social experiment Electoral District 2150 Yes Malawi Social experiment Village Cluster 3200 Yes Zambia Social experiment Community Welfare Assistance Committee 2519 No Ethiopia Non-experimental (PSM and IPW) Household level within a village 3351 Yes Ghana Non-experimental (PSM and IPW) Household and Region 1504 No Evaluation of SCT in SSA - Design All studies are longitudinal with a baseline and at least one post-intervention follow-up.
  10. 10. • Real-world evaluation of government-run cash transfer programs in seven countries (not rarified experiments) • Malawi, Ghana, Ethiopia, Lesotho, Zambia and Kenya • 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) • Integrates general-equilibrium and econometric methods • Data: • Baseline surveys • Comparison of treatment & control groups • Simulations of SCT impacts • Qualitative methods • Follow-on surveys • Estimation of actual SCT impacts • Validation, updating of simulation models The Mixed Method Approach Eligible Ineligible Eligible Ineligible TreatmentVillage ControlVillage
  11. 11. What are the key findings?
  12. 12. Livelihoods matter for social cash transfers beneficiaries • Most beneficiaries in Sub Saharan Africa are rural, engaged in agriculture and work for themselves • >80% produce crops; >50% have livestock • Most grow local staples, traditional technology and low levels of modern inputs • Most production consumed on farm • Most have low levels of productive assets • few hectares of land, a few animals, basic tools, few years of education • Engaged on farm, non-farm business, casual wage labour (ganyu) • Often labour-constrained • Elderly, single headed household • Large share of children work on the family farm • 50% in Zambia, 30% in Lesotho, 42% in Kenya
  13. 13. Households invest in livelihood activities— though impact varies by country Zambia Malawi Kenya Lesotho Ghana Agricultural inputs +++ - ++ +++ Agricultural tools +++ +++ NS NS NS Agricultural production +++ NS ++ NS Sales +++ NS NS NS - - Home consumption of agricultural production NS +++ +++ NS Livestock ownership All types All types Small NS NS Non-farm enterprise +++ NS +FHH -MHH - NS Stronger impact Mixed impact Less impact
  14. 14. Improved ability to manage risk Zambia Kenya Malawi Ghana Lesotho Negative risk coping - - - - - - Pay off debt +++ +++ NS Borrowing - - - NS - - - NS Purchase on credit NS NS NS Savings +++ +++ +++ NS Give informal transfers NS +++ +++ Receive informal transfers NS +++ Remittances - - - NS - - - Trust (towards leaders) Strengthened social networks • In all countries, re-engagement with social networks of reciprocity— informal safety net • Allow households to participate, to “mingle” again • Reduction in negative risk coping strategies • Increase in savings, paying off debt and credit worthiness—risk aversion • Some instances of crowding out
  15. 15. Total expenditure Food expenditure Non-food expenditure Total caloric intake Dietary Diversity Score HH received SCT NS NS NS NS ++ (-ve) rainfall shock - - - - - - - - - - - - NS CGP*rainfall shock +++ +++ +++ +++ +++ Notes: NS = not significant; + = significant positive impact; – = significant negative impact. One, two or three ‘+’ or ‘–‘ signs refer to significance at, respectively 10, 5 or 1 percent confidence level. Heterogeneous impact of CT on welfare - GLS-RE 15 Does CT mitigate adverse effect of weather shock? Cash transfer mitigate the negative effect of climate shock
  16. 16. a) Daily Caloric Intake b) Food Expenditure c) Non Food Expenditure Magnitude of CT effect across quantiles CT mitigate the negative effect of climate shock espcially for the poorest
  17. 17. Impact on food security Ghana Lesotho Kenya Malawi Zambia Ethiopia Food security +++ +++ N/A +++ +++ +++ Consumption NS + +++ +++ +++ ++ Dietary diversity 0 NS +++ +++ ++ + Home consumption of crop production N/E N/E +++ NS + N/E Littleimpact Big impact, partially through increased agricultural production
  18. 18. Crop Livestock NFE Productive labor Social Network Zambia yes yes yes yes Malawi yes yes no yes small Kenya no small yes yes Lesotho yes small no no yes Ghana no no no small yes WHAT ARE KEY FINDINGS? 18 What explains differences in household-level impact across countries?
  19. 19. Predictability of payment Regular and predictable transfers facilitate planning, consumption smoothing and investment 0 1 Sep-10 Nov-10 Jan-11 Mar-11 May-11 Jul-11 Sep-11 Nov-11 Jan-12 Mar-12 May-12 Jul-12 Sep-12 #ofpayments Zambia CGP 0 1 2 3 4 5 6 #ofpayments Ghana LEAP Regular and predictableLumpy and irregular 19
  20. 20. Bigger transfer means more impact 0 5 10 15 20 25 30 35 40 Ghana LEAP (old) Kenya CT- OVC (big) Burkina Kenya CT- OVC RSA CSG Lesotho CGP (base) Ghana LEAP (current) Kenya CT- OVC (small) Zim (HSCT) Zambia CGP Zambia MCP Malawi SCT Widespread impact Selective impact %orpercapitaincomeofpoor 20
  21. 21. Demographic profile of beneficiaries Under 5 5 to 9 10 to 14 15 to 19 20 to 24 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64 65 to 69 70 to 74 75 to 79 80 to 84 85 to 89 Over 90 1000 500 500 1000population Males Females Ghana LEAP Under 5 5 to 9 10 to 14 15 to 19 20 to 24 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64 65 to 69 70 to 74 75 to 79 80 to 84 85 to 89 Over 90 2000 500 500 2000population Males Females Zambia CGP More able-bodiedMore labour-constrained 21
  22. 22. Key messages 1. Overall positive effect of the CT on welfare, livelihood activities and Food security; though heterogenous across countries 2. CT mitigates against the negative effects of extreme weather events (negative shocks)… 3. … this effect is higher for lowest quantiles of the distribution. 4. Transfer size, predictability, demographic profile and complementary intervention is key to maximize the impact
  23. 23. Thank you! sasfaw@gcfund.org @GCF_Eval

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