The impact of social cash transfers on 
labour market outcomes: 
the evidence from sub-Saharan Africa 
Benjami n Davis 
Fo...
Why are social cash transfers relevant 
for labour outcomes? 
• Most beneficiaries in Sub Saharan Africa are rural, 
engag...
Production and consumption decisions 
are interdependent 
• Work in context of multiple market failures in credit, 
insura...
Policy makers are concerned about 
Dependency
Why social cash transfers targeted to poorest 
of the poor can affect labour market outcomes 
• Long term effects of impro...
Countries/evaluations 
included in this review 
• Malawi 
– Mchinji pilot, 2008-2009 
– SCT Expansion, 2013-2015 
• Kenya ...
Households invest in livelihood activities— 
though impact varies by country 
Zambia Malawi Kenya Lesotho Ghana Tanz 
Agri...
Shift from casual wage labor to on farm 
and family productive activities 
adults Zambia Kenya Malawi Lesotho Ghana Tanz 
...
Improved ability to manage risk 
Zambia Kenya Malawi Ghana Lesotho Tanz 
Negative risk coping - - - - - - 
Pay off debt ++...
What explains differences in impact 
across countries? 
Crop Livestock NFE Productive 
labor 
Social 
Network 
Zambia yes ...
Predictability of payment 
Lumpy and irregular Regular and predictable 
1 
0 
# of payments 
Zambia CGP 
Regular and predi...
Bigger transfer means more impact 
40 
35 
30 
25 
20 
15 
10 
5 
0 
Ghana 
LEAP 
(old) 
Kenya 
CT-OVC 
(big) 
Burkina Ken...
Demographic profile of beneficiaries 
More labour-constrained More able-bodied 
Ghana LEAP 
Over 90 
85 to 89 
80 to 84 
7...
Economic context matters 
• Vibrant and dynamic local economy? 
• Opportunities awaiting if only a bit more liquidity? 
Pr...
Beneficiaries are hard working and are responsible 
for their own income generation and food security 
What are the implic...
Our websites 
From Protection to Production Project 
http://www.fao.org/economic/PtoP/en/ 
The Transfer Project 
http://ww...
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Benjamin Davis: The impact of social cash transfers on labour market outcomes the evidence from sub saharan africa

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This presentation is part of the programme of the International Seminar "Social Protection, Entrepreneurship and Labour Market Activation: Evidence for Better Policies", organized by the International Policy Centre for Inclusive Growth (IPC-IG/UNDP) together with Canada’s International Development Research Centre (IDRC) and the Colombian Think Tank Fedesarrollo held on September 10-11 at the Ipea Auditorium in Brasilia.




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Benjamin Davis: The impact of social cash transfers on labour market outcomes the evidence from sub saharan africa

  1. 1. The impact of social cash transfers on labour market outcomes: the evidence from sub-Saharan Africa Benjami n Davis Food and Agriculture Organization, the From Protection to Production Project, and the Transfer Project Social protection, entrepreneurship and labour market activation Evidence for better policies International Seminar and Policy Forum IPEA Headquarters, Brasilia September 10-11, 2014
  2. 2. Why are social cash transfers relevant for labour outcomes? • Most beneficiaries in Sub Saharan Africa are rural, engaged in agriculture and work for themselves – Zimbabwe: 88% produce crops; 75% have livestock – Kenya: 80% produce crops; 75% have livestock – Lesotho: 80% produce crops; 60% have livestock – Zambia: 80% produce crops; 50% have livestock • Most grow local staples, using traditional technology and low levels of modern inputs – Most production consumed on farm • Most have low levels of productive assets – .5 -2 hectares of agricultural land, a few animals, basic agricultural tools, few years of education • Engaged on farm, non farm business, casual wage labour (ganyu/maricho) • Large share of children work on the family farm – 50% in Zambia
  3. 3. Production and consumption decisions are interdependent • Work in context of multiple market failures in credit, insurance, etc – Constrain economic decisions in investment, production, labor allocation, risk taking • Short time horizon—imperative of meeting immediate needs • Lack of liquidity, difficult to manage risk – Decisions about production and consumption linked • ͞ŶoŶ separability͟ of produĐtioŶ aŶd ĐoŶsuŵptioŶ ŵeaŶs that social objectives are conditioned by livelihoods—and vice versa – Labor needs (adults and children), including domestic chores – Investment in schooling and health – Food consumption, dietary diversity and nutrition – Intra household decision making • Dynamic between men and women, old and young
  4. 4. Policy makers are concerned about Dependency
  5. 5. Why social cash transfers targeted to poorest of the poor can affect labour market outcomes • Long term effects of improved human capital – Nutritional and health status; educational attainment – Labor productivity and employability • Transfers can relax some of constraints brought on by market failure (lack of access to credit, insurance) – Helping households manage risk – Providing households with liquidity • Transfers can reduce burden on social networks and informal insurance mechanisms
  6. 6. Countries/evaluations included in this review • Malawi – Mchinji pilot, 2008-2009 – SCT Expansion, 2013-2015 • Kenya – CT OVC, 2007-2011 • Zambia – Child Grant, 2010-2014 • Ethiopia – Tigray SPP, 2012-2014 • Ghana – LEAP, 2010-2012 • Lesotho – CGP, 2011-2013 • Zimbabwe – HSCT, 2013-2014 • Tanzania – TASAF Pilot, 2009-2012 Mixed method approach • Household and individual level impacts via econometric methods (experimental and non experimental) • Perceptions on household economy and decision making, social networks, local community dynamics and operations via qualitative methods • Local economy effects via LEWIE (GE) modeling Still waiting for household level analysis from: • Zimbabwe (end 2014) • Ethiopia (end 2014) • Malawi (early 2015) • Zambia three year follow up (end 2014)
  7. 7. Households invest in livelihood activities— though impact varies by country Zambia Malawi Kenya Lesotho Ghana Tanz Agricultural inputs +++ - ++ +++ (1) Agricultural tools +++ +++ NS NS NS Agricultural production +++(2) NS ++(3) NS Sales +++ NS NS NS - - Home consumption of agricultural production NS +++ +++ (4) NS NS Livestock ownership All types All types Small PIgs NS Small Non farm enterprise +++ NS +FHH -MHH - NS 1) Reduction hired labor 2) Overal value of production; reduction in cassava 3) Maize, sorghum and garden plot vegetables 4) Animal products Stronger impact Mixed impact Less impact
  8. 8. Shift from casual wage labor to on farm and family productive activities adults Zambia Kenya Malawi Lesotho Ghana Tanz Agricultural/casual wage labor - - - - - - (1,2) - - - - - (2) NS Family farm + (2) ++ (1) +++ ++ (2) +++ Non farm business +++ NS + NS Non agricultural wage labor +++ NS NS NS NS children Wage labor NS NS - - - NS NS (6) Family farm NS - - - (4) +++ (5) - - NS (6) 1) Positive farther away 2) Varies by age, gender 3) Particularly males 4) Particularly older boys 5) Increase chores, reduction leisure 6) No impact on time use; labor not reported No clear picture on child labor (but positive impacts on schooling) Shift from casual wage labour to family business—consistently reported in qualitative fieldwork
  9. 9. Improved ability to manage risk Zambia Kenya Malawi Ghana Lesotho Tanz Negative risk coping - - - - - - Pay off debt +++ +++ NS Borrowing - - - NS - - - NS NS Purchase on credit NS NS NS Savings +++ +++ +++ NS ++ poorest Give informal transfers NS +++ +++ Receive informal transfers NS +++ Remittances - - - NS - - - NS (1) Trust (towards leaders) ++ Strengthened social networks • In all countries, re-engagement with social networks of reciprocity— informal safety net • Allow households to participate, to ͞ŵiŶgle͟ agaiŶ • Reduction in negative risk coping strategies • Increase in savings, paying off debt and credit worthiness—risk aversion • Some instances of crowding out 1) Mixes remittances and informal transfers
  10. 10. What explains differences in impact across countries? 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 Tanzania small
  11. 11. Predictability of payment Lumpy and irregular Regular and predictable 1 0 # of payments Zambia CGP Regular and predictable transfers facilitate planning, consumption smoothing and investment 6 5 4 3 2 1 0 # of payments Ghana LEAP
  12. 12. Bigger transfer means more impact 40 35 30 25 20 15 10 5 0 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 % or per capita income of poor
  13. 13. Demographic profile of beneficiaries More labour-constrained More able-bodied Ghana LEAP Over 90 85 to 89 80 to 84 75 to 79 70 to 74 65 to 69 60 to 64 55 to 59 50 to 54 45 to 49 40 to 44 35 to 39 30 to 34 25 to 29 20 to 24 15 to 19 10 to 14 5 to 9 Under 5 1000 500 population 500 1000 Males Females Zambia CGP Over 90 85 to 89 80 to 84 75 to 79 70 to 74 65 to 69 60 to 64 55 to 59 50 to 54 45 to 49 40 to 44 35 to 39 30 to 34 25 to 29 20 to 24 15 to 19 10 to 14 5 to 9 Under 5 2000 50 p0opulatio5n0 0 2000 Males Females
  14. 14. Economic context matters • Vibrant and dynamic local economy? • Opportunities awaiting if only a bit more liquidity? Programme messaging matters • Messaging in unconditional programmes, and conditions in CCTs, affects how households spend the transfer • Lesotho: CGP transfer combined with Food Emergency Grant – Instructed to spend on children (shoes and uniforms) – Instructed to spend on agricultural inputs – And they did!!
  15. 15. Beneficiaries are hard working and are responsible for their own income generation and food security What are the implications for labour market outcomes? 1. Clear impact on household labour allocation, in context of liquidity constraints • Off and on farm, adult and child 2. No evidence of impact on wages or prices—yet • Prograŵs iŶ this reǀieǁ are Ŷot ͞ďig͟ eŶough to affeĐt loĐal wages or prices 3. Heterogeneity of impact – Gender, labour constraint
  16. 16. Our websites From Protection to Production Project http://www.fao.org/economic/PtoP/en/ The Transfer Project http://www.cpc.unc.edu/projects/transfer

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