innovations for poverty action evaluating the impact of agricultural development programs africa...
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Innovations for Poverty Action
Evaluating the Impact of Agricultural Development Programs
Africa Rising23 October 2012
Agenda
Introduction: IPA and our research methods
IPA Agricultural Research Projects
M&E Tools
The Way Forward
Introduction
Introduction to IPA and IPA’s research methods
What does IPA do?
Established in 2002 to measure the effects of poverty alleviation programs Uses the randomized controlled trial (RCT) method
of rigorous evaluation Works in the areas of agriculture, health, education,
microfinance, water and sanitation, and governance Openly shares findings about what does and doesn’t
work with policymakers, donors, practitioners, researchers and other critical stakeholders
Established in Ghana in 2007 Ongoing national and regional projects in
agriculture, education, health and microfinance
What is randomized control trial evaluation?
Control Treatment
Impact
Our Approach
We generate insights on what works and what does not through randomized evaluations, and ensure that those findings will be useful to, and used by practitioners and policy makers
Innovate Evaluate Replicate Communi-cate Scale
- Understand market failures-Develop innovative solutions to poverty- Use frontier knowledge from economics, and psychology
Randomized Controlled Trials-Impact evaluations- Comparing variations of an intervention- Experiment with product designs
Replicate evaluations in various settings to :- Generalize research findings - Tell practitioners what works (and not), when
Effectively communicate to practitioners: -Conferences-Workshops with policy makers and practitioners-Policy memos and focus notes
Facilitate scale-up of effective solutions :- Active policy outreach -Practitioners’ toolkits - Hands-on technical assistance
• Surprisingly little hard evidence on what works
• Can do more with given budget with better evidence
• If people knew money was going to programs that worked, could help increase pot for anti-poverty programs
• We should be asking:• Which programs work best, why and when?• How can we scale up what works?
Why Impact Evaluation?
IPA Agricultural Research Projects
Examining Underinvestment in Agriculture
Background: EUI (2008-2012)
Research design EUI: Examining Underinvestment in Agriculture Investigators: economists at Yale and Ghana Legon Question: why do smallholders underinvest in farms? Hypotheses: capital constraints and risk aversion Treatments: unconditional cash grants and rainfall
index insurance Findings
Investment effects: insurance significantly increased farm investment, while capital alone did not
Profitability effects: higher investment did not lead to higher farm profitability
Insurance demand: high, when priced reasonably
IPA Agricultural Research Projects
Disseminating Innovative Resources and Technologies to
Smallholders
EUI and DIRTS
Questions that arise from EUI results: How can we take advantage of increased investment by
insured farmers? How can farmers move away from risk-averse farming
techniques, and towards profit maximization? What influences investment decisions? Information?
Access to fertilizer and seeds?
Background: DIRTS (2013-2014)
Research design DIRTS: Disseminating Innovative Resources and
Technologies to Smallholders Investigators: economists at Yale, UDS, SARI, IFPRI Question: building on EUI findings, why are smallholder
farm productivity and profitability levels so low, even when investment increases?
Hypotheses: risk aversion, limited access to quality inputs, limited access to good information
Treatments: varying combinations of: (1) drought index insurance (2) access to improved-yield technologies and (3) Community Extension Agent (CEA) program
IPA Agricultural Research Projects
Community Extension Agent Pilot
CEA: Community Extension Agent program Partners: IPA, MoFA, NRGP, Grameen Foundation Objective: complement existing extension services by training
community members to use Android phones to provide better information resources to farmers. CEAs will be connected to AEAs, providing a link between
AEAs and the community. Improved information developed in content workshops with
key stakeholders and experts made available through Grameen application
Messaging allows for improved communication between supervisors, CEAs, AEAs, and community farmers
Training provided through modules sent via phones Collecting quality data through survey app
Background: CEA pilot (2012)
The Way Forward
Partnership Opportunities
Partnership Opportunities: What we bring
Program evaluation study design
Survey data collection
M&E tools Paper Electronic Data quality protocols
Partnership Opportunities: What we are looking for
On current projects: Integrating agricultural research findings into best practices
resources Identifying context-relevant technology input packages to test Designing mobile extension programs Designing community extension agent programs
Future project interests: Identifying promising solutions for increasing farmer investment and
profitability for evaluation Childhood nutrition Other issues of importance to development partners?
Contact Information
Annie Smith ◦ rsmith@poverty-action.orgSenior Project Associate
Elizabeth Schultz◦ eschultz@poverty-action.orgGhana Research Cluster Manager
M&E Tools
M&E Tools: Quality Data for Quality Evaluation
M&E tools: Why?
Is the program being implemented? Record keeping by implementing agents Spot checks Interviews with program recipients Spending tracking
Is the program influencing outcomes as measured by key indicators? Administrative data (eg. Fertilizer sales) Survey data (eg. Farmer-reported use of fertilizer) Observational data (eg. Fertilizer use witnessed by
enumerators)
M&E tools: How?
Paper: low investment, easy to teach Field monitoring records Paper surveys
Electronic: fast, additional data collection capabilities Netbooks: electronic surveys Mobile: automatic recording of database use patterns by
CEAs Mobile: collection of GPS coordinates for monitoring Mobile: frequent labor use data collection by CEAs
M&E tools: Ensuring Quality
Collect the right data
Is the data source biased?
Does the data source have the capacity to do quality data collection?TimeTraining ToolsFunds
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