Dissemination of new agricultural technologies in africa making extension work
Dissemination of new agricultural technologies inAfrica: making extension workAn RCT based on ICRAF-Makerere University-PSE collaborationJane 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 inNairobi Identification of common ground andinterests 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 ofagricultural technologies in SSA: address lack of information and training pass-on technologies developed by researchinstitutes 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 servicesto dairy farmers in Uganda impacts of original program on technologyadoption, productivity and welfare And variations addressing some of themain(?) constraints: improving incentives access to information/upstream linkages farm(er) heterogeneity and possible returns tocustomization
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 improvedanimal feeds disseminate this information through demonstration plots, access toseeds/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 formulationof seeds hay and silage making Some evidence of potentially large returns totheir use from on-farm trials, small sample household surveys,focus groups, case studies But also scope for increased adoption amongsome groups women in particular
What do we want to show?Overall impact of the FT program Impacts on dairy production yields, dairyincome, and other welfare indicators Analysis: effects on technology adoption, includingselection 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 providinginformation on good technologies compared to withoutprogram? Compare same individual with & without programsat the same point in time BUT: Never observe same individual with andwithout program at same point in time
Solving the evaluation problem Counterfactual: what would havehappened without the program Need to estimate counterfactual i.e. find a control or comparison group Counterfactual Criteria Treated & counterfactual groups have identical initialcharacteristics on average, Only reason for the difference in outcomes is due to theintervention
InitialPopulationQuintile I(Poor)Quintile II Quintile III Quintile IV QuintileV(Rich)Selection biasSelectionImpact ≠ Y Trait – Y ControlTreatment groupControl group
InitialPopulationSelectionTreatment group(program beneficiaries)Impact = Y Treat – Y ControlQuintile I(poor)Quintile II Quintile III Quintile IV QuintileV(rich)Randomized selectionControl group(don’t benefit from the program)
But we also want to know (and test)… How to potentially increase theeffectiveness of the FT program by testingvariations of the original design=> Design variations that can be implementedwithin the overall FT program to shed light onunderlying mechanisms=> Randomly allocate them across FTs in orderto test their relative effectiveness
Variation 1: incentives Some FTs, in addition to a basic set of non-monetary rewards, are encouraged to worktowards specific targets and receive incentives fordoing so Specific incentives to be defined: trainings (e.g. studytours), material (planting material, seeds), socialcapital, 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 andeffectiveness of dissemination activities?
Variation 2: linkages to professionalextension agents Link FTs with extension professionals who provide tutoring and expert advice monitor their activities How Specific extension agent in an DFBA for backstoppingrandom subset of FTs through farm visits extension agents and subset of FTs meet for quarterlymeetings Analysis: seek ways to improve FTs skills (+ training material)and access to new knowledge (from public services orprivate providers) effects on knowledge, career, activities andeffectiveness 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 assesstheir needs and target content of refresher trainings Analysis: effects on participation to FT dissemination activities, notablyamong marginalized groups? on returns to FT program? Is cost-effectivenessmodified?
Evaluation approach:RCT with orthogonal randomization DFBAs organized in dairy interest groups(DIG~3/4 villages) FT program incorporation evaluated at sub-DFBAlevel (~9 DIGs) Incentives variation at the DFBA level Linkage variation randomized at the FT level Customization variation randomized at the levelof DIG or pairs of DIGs
Data to be collected Quantitative data Baseline survey of 2640 sample of farmersprior to randomization, stratified by genderand assets holdings (2013) Follow-up surveys 1.5 (early 2015) and 3years (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 arepractically feasible and get as much aspossible 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 widerrelevance Capacity building Research collaboration – learning-by-doing Policy Policy inception meeting Stakeholder consultation/involvement Lessons potentially of broad relevance forextension approaches, beyond FT