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Dissemination of new agricultural technologies in
Africa: making extension work
An RCT based on ICRAF-Makerere University-PSE collaboration
Jane Kugonza, Rick Kamugisha (ICRAF)
Monica Karuhanga and Margaret Mangheni (Makerere University)
Luc Behaghel, Jeremie Gignoux, Karen Macours (PSE)
With special thanks to continuous support from Steve Franzel
How did we get to this project?
 It all started here! ATAI (CEGA-JPAL)
training on impact evaluation in Jan 2012 in
Nairobi
 Identification of common ground and
interests
 Lot’s of phone and skype calls
 Proposal development
 3ie funding
 First team meeting in Jan 2013 in Kampala
What is it about?
Technology dissemination
 Role for extension to increase adoption of
agricultural technologies in SSA:
 address lack of information and training
 pass-on technologies developed by research
institutes
 Many challenges and constraints
~ extension “pessimism”
 But also many innovative models out there
– with little hard evidence on their impacts
Research Project Goal
 Evaluate the impacts of a Farmer Trainer
(FT) program providing extension services
to dairy farmers in Uganda
 impacts of original program on technology
adoption, productivity and welfare
 And variations addressing some of the
main(?) constraints:
 improving incentives
 access to information/upstream linkages
 farm(er) heterogeneity and possible returns to
customization
ICRAF’s FT program
 A component of the East African Dairy Development project
 FTs are
 volunteers selected by dairy farmers business associations
 based on communication skills and social capital
 trained in different practices for production and use of improved
animal feeds
 disseminate this information through demonstration plots, access to
seeds/planting material and teaching
 To approximately 30 farmers per FT
 2nd phase of the program starting in 2013 (?)
 ~1000 FTs in 35 DFBAs trained in phase 1 (2008-12)
 ~2000 more in +/- 60 DFBAs in phase 2 (2013-18)
Technologies promoted
 A set of feeding practices
 growing of specific fodder grasses (e.g. elephant grass,
caliandra), shrubs, sweet potato vines, and formulation
of seeds
 hay and silage making
 Some evidence of potentially large returns to
their use
 from on-farm trials, small sample household surveys,
focus groups, case studies
 But also scope for increased adoption among
some groups
 women in particular
What do we want to show?
Overall impact of the FT program
 Impacts on dairy production yields, dairy
income, and other welfare indicators
 Analysis:
 effects on technology adoption, including
selection of adopters
 returns in the short and medium runs
 cost-effectiveness analysis
Assessing impact
 Examples
 How much do extension services increase yields?
 What are agricultural revenues with program providing
information on good technologies compared to without
program?
 Compare same individual with & without programs
at the same point in time
 BUT: Never observe same individual with and
without program at same point in time
Solving the evaluation problem
 Counterfactual: what would have
happened without the program
 Need to estimate counterfactual
 i.e. find a control or comparison group
 Counterfactual Criteria
 Treated & counterfactual groups have identical initial
characteristics on average,
 Only reason for the difference in outcomes is due to the
intervention
Initial
Population
Quintile I
(Poor)
Quintile II Quintile III Quintile IV QuintileV
(Rich)
Selection bias
Selection
Impact ≠ Y Trait – Y Control
Treatment group
Control group
Initial
Population
Selection
Treatment group
(program beneficiaries)
Impact = Y Treat – Y Control
Quintile I
(poor)
Quintile II Quintile III Quintile IV QuintileV
(rich)
Randomized selection
Control group
(don’t benefit from the program)
But we also want to know (and test)
…
 How to potentially increase the
effectiveness of the FT program by testing
variations of the original design
=> Design variations that can be implemented
within the overall FT program to shed light on
underlying mechanisms
=> Randomly allocate them across FTs in order
to test their relative effectiveness
Variation 1: incentives
 Some FTs, in addition to a basic set of non-
monetary rewards, are encouraged to work
towards specific targets and receive incentives for
doing so
 Specific incentives to be defined: trainings (e.g. study
tours), material (planting material, seeds), social
capital, recognition?
 Tournament between FT from same DFBA
 Analysis effects of incentives on
 FTs' 'career' (some can drop out),
 selection of farmers targeted by FTs, and intensity and
effectiveness of dissemination activities?
Variation 2: linkages to professional
extension agents
 Link FTs with extension professionals who
 provide tutoring and expert advice
 monitor their activities
 How
 Specific extension agent in an DFBA for backstopping
random subset of FTs through farm visits
 extension agents and subset of FTs meet for quarterly
meetings
 Analysis:
 seek ways to improve FTs skills (+ training material)
and access to new knowledge (from public services or
private providers)
 effects on knowledge, career, activities and
effectiveness of FTs?
Variation 3: customization
 How to customize extension services?
 Target content of refresher training
 Module in refresher training farmer-by-farmer needs assessment
 quarterly consultations of farmer members in their DIG to assess
their needs and target content of refresher trainings
 Analysis: effects on
 participation to FT dissemination activities, notably
among marginalized groups?
 on returns to FT program? Is cost-effectiveness
modified?
Evaluation approach:
RCT with orthogonal randomization
 DFBAs organized in dairy interest groups
(DIG~3/4 villages)
 FT program incorporation evaluated at sub-DFBA
level (~9 DIGs)
 Incentives variation at the DFBA level
 Linkage variation randomized at the FT level
 Customization variation randomized at the level
of DIG or pairs of DIGs
Data to be collected
 Quantitative data
 Baseline survey of 2640 sample of farmers
prior to randomization, stratified by gender
and assets holdings (2013)
 Follow-up surveys 1.5 (early 2015) and 3
years (2016) after first FTs trained
 Census survey of 660 FTs at midline
 How much data and on whom?
 Power for identifying effects for specific subgroups
(by gender and assets holdings)
 Complementary qualitative data collection
Challenges
 How to design variations that are
practically feasible and get as much as
possible to mechanism we want to test
 Start from field observations
 Resource constraints ($, staff time, …)
 Role of field coordinator
 Flexible timing
 E.g. potentially rolling baseline
Evaluation for what?
 Answers to important questions with wider
relevance
 Capacity building
 Research collaboration – learning-by-doing
 Policy
 Policy inception meeting
 Stakeholder consultation/involvement
 Lessons potentially of broad relevance for
extension approaches, beyond FT

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Dissemination of new agricultural technologies in africa making extension work

  • 1. Dissemination of new agricultural technologies in Africa: making extension work An RCT based on ICRAF-Makerere University-PSE collaboration Jane Kugonza, Rick Kamugisha (ICRAF) Monica Karuhanga and Margaret Mangheni (Makerere University) Luc Behaghel, Jeremie Gignoux, Karen Macours (PSE) With special thanks to continuous support from Steve Franzel
  • 2. How did we get to this project?  It all started here! ATAI (CEGA-JPAL) training on impact evaluation in Jan 2012 in Nairobi  Identification of common ground and interests  Lot’s of phone and skype calls  Proposal development  3ie funding  First team meeting in Jan 2013 in Kampala
  • 3. What is it about? Technology dissemination  Role for extension to increase adoption of agricultural technologies in SSA:  address lack of information and training  pass-on technologies developed by research institutes  Many challenges and constraints ~ extension “pessimism”  But also many innovative models out there – with little hard evidence on their impacts
  • 4. Research Project Goal  Evaluate the impacts of a Farmer Trainer (FT) program providing extension services to dairy farmers in Uganda  impacts of original program on technology adoption, productivity and welfare  And variations addressing some of the main(?) constraints:  improving incentives  access to information/upstream linkages  farm(er) heterogeneity and possible returns to customization
  • 5. ICRAF’s FT program  A component of the East African Dairy Development project  FTs are  volunteers selected by dairy farmers business associations  based on communication skills and social capital  trained in different practices for production and use of improved animal feeds  disseminate this information through demonstration plots, access to seeds/planting material and teaching  To approximately 30 farmers per FT  2nd phase of the program starting in 2013 (?)  ~1000 FTs in 35 DFBAs trained in phase 1 (2008-12)  ~2000 more in +/- 60 DFBAs in phase 2 (2013-18)
  • 6. Technologies promoted  A set of feeding practices  growing of specific fodder grasses (e.g. elephant grass, caliandra), shrubs, sweet potato vines, and formulation of seeds  hay and silage making  Some evidence of potentially large returns to their use  from on-farm trials, small sample household surveys, focus groups, case studies  But also scope for increased adoption among some groups  women in particular
  • 7. What do we want to show? Overall impact of the FT program  Impacts on dairy production yields, dairy income, and other welfare indicators  Analysis:  effects on technology adoption, including selection of adopters  returns in the short and medium runs  cost-effectiveness analysis
  • 8. Assessing impact  Examples  How much do extension services increase yields?  What are agricultural revenues with program providing information on good technologies compared to without program?  Compare same individual with & without programs at the same point in time  BUT: Never observe same individual with and without program at same point in time
  • 9. Solving the evaluation problem  Counterfactual: what would have happened without the program  Need to estimate counterfactual  i.e. find a control or comparison group  Counterfactual Criteria  Treated & counterfactual groups have identical initial characteristics on average,  Only reason for the difference in outcomes is due to the intervention
  • 10. Initial Population Quintile I (Poor) Quintile II Quintile III Quintile IV QuintileV (Rich) Selection bias Selection Impact ≠ Y Trait – Y Control Treatment group Control group
  • 11. Initial Population Selection Treatment group (program beneficiaries) Impact = Y Treat – Y Control Quintile I (poor) Quintile II Quintile III Quintile IV QuintileV (rich) Randomized selection Control group (don’t benefit from the program)
  • 12. But we also want to know (and test) …  How to potentially increase the effectiveness of the FT program by testing variations of the original design => Design variations that can be implemented within the overall FT program to shed light on underlying mechanisms => Randomly allocate them across FTs in order to test their relative effectiveness
  • 13. Variation 1: incentives  Some FTs, in addition to a basic set of non- monetary rewards, are encouraged to work towards specific targets and receive incentives for doing so  Specific incentives to be defined: trainings (e.g. study tours), material (planting material, seeds), social capital, recognition?  Tournament between FT from same DFBA  Analysis effects of incentives on  FTs' 'career' (some can drop out),  selection of farmers targeted by FTs, and intensity and effectiveness of dissemination activities?
  • 14. Variation 2: linkages to professional extension agents  Link FTs with extension professionals who  provide tutoring and expert advice  monitor their activities  How  Specific extension agent in an DFBA for backstopping random subset of FTs through farm visits  extension agents and subset of FTs meet for quarterly meetings  Analysis:  seek ways to improve FTs skills (+ training material) and access to new knowledge (from public services or private providers)  effects on knowledge, career, activities and effectiveness of FTs?
  • 15. Variation 3: customization  How to customize extension services?  Target content of refresher training  Module in refresher training farmer-by-farmer needs assessment  quarterly consultations of farmer members in their DIG to assess their needs and target content of refresher trainings  Analysis: effects on  participation to FT dissemination activities, notably among marginalized groups?  on returns to FT program? Is cost-effectiveness modified?
  • 16. Evaluation approach: RCT with orthogonal randomization  DFBAs organized in dairy interest groups (DIG~3/4 villages)  FT program incorporation evaluated at sub-DFBA level (~9 DIGs)  Incentives variation at the DFBA level  Linkage variation randomized at the FT level  Customization variation randomized at the level of DIG or pairs of DIGs
  • 17. Data to be collected  Quantitative data  Baseline survey of 2640 sample of farmers prior to randomization, stratified by gender and assets holdings (2013)  Follow-up surveys 1.5 (early 2015) and 3 years (2016) after first FTs trained  Census survey of 660 FTs at midline  How much data and on whom?  Power for identifying effects for specific subgroups (by gender and assets holdings)  Complementary qualitative data collection
  • 18. Challenges  How to design variations that are practically feasible and get as much as possible to mechanism we want to test  Start from field observations  Resource constraints ($, staff time, …)  Role of field coordinator  Flexible timing  E.g. potentially rolling baseline
  • 19. Evaluation for what?  Answers to important questions with wider relevance  Capacity building  Research collaboration – learning-by-doing  Policy  Policy inception meeting  Stakeholder consultation/involvement  Lessons potentially of broad relevance for extension approaches, beyond FT