Can Information Help Farmers
Adopt New Technologies?
Jeremy Magruder, UCB
World Bank, Washington DC
December 10, 2015
Evidence from Eight Countr ies in Afr ica
and Asia
Overview
• Constraints for Agricultural Technology Adoption
• Background on ATAI
• Importance of Information
• Policy Lessons I: Agricultural Extension
• Policy Lessons II: Price Information
• Conclusion
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Cereal Yields (Metric Tons/Hectare)
0
1
2
3
4
5
6
7
8
Sub-Saharan Afria
East Asia
South Asia
U.S.
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Fertilizer Use (Metric Tons/Hectare)
0
10
20
30
40
50
60
70
80
Sub-Saharan Africa
East Asia
South Asia
U.S.
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
What is hampering
technology adoption?
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Market Inefficiencies
1. Credit markets
2. Risk markets
3. Information
4. Input and output markets
5. Externalities
6. Labor markets
7. Land markets
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
About ATAI
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Since the Start of ATAI
Category Total
Farmers surveyed 108,814
Female farmers surveyed 47,819
Farmers whose behavior has changed 17,681
ATAI Awards 51
Unique ATAI projects 40
Countries with ATAI projects 14
Researchers on ATAI projects 89
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
The Process
ATAI Review Paper
• Written in ATAI’s first year; updated annually
• Summarizes everything we know about the 7 constraints to agricultural technology adoption
Evidence Inventory
• Hired graduate students (UCB & MIT) to build database of papers (in Sharepoint)
• Classified studies by: constraint, intervention, technology, country, and identification strategy and one-sentence summaries
Summary Documents
• ATAI staff and board officers
• Summaries of lessons in risk, credit, and information
Materials
• Developed two-pagers and adaptable Powerpoint to disseminate lessons externally
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Preview: Information
• General extension often leaves room for
improvement
• Extension may be improved• Incentives
• Feedback
• Technology
• Leveraging social networks
• Price Information• Must be new to have an effect
• Intermediaries/market structure
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Why do farmers need information?
• Information helps famers assess novel
technologies, their risk profile and potential
profitability
• If a farmer is to use a new technology
effectively they need to know:
1. That it exists
2. Something about its benefits and costs
3. How to use it effectively
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
How do farmers receive information?
• Government or NGO extension services
• Test plots
• Trainings
• Agro-dealers
• Social learning
• Direct to farmers
• Door-to-door
• ICT
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
How could information be the
binding constraint?
• A natural question: if there are profitable
technologies, why don’t farmers find out
about them without any intervention?
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
What is needed for adoption?
• Suppose farmers witness high yields on a plot planted with a new technology
• How do they know what their yield (or, profit) would look like?
• Need to know:
• Plot characteristics (would this work on their plot?)
• Input choices (would this work with their input use?)
• Expected yields if the weather were different
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Profits vs. Yields
Governments and NGOs
provide advice is designed
to maximize yield, rather
than maximize farmer profit
Farmer decisions are
based on profit, not yield
Duflo et al 2008, Hanna et al 2013
Governments and NGOsMaximize
YIELD
FarmersMaximize
PROFIT
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Often, traditional extension has
limited effects
• Traditional extension often has relatively
low impacts on adoption
• Test plots
• Farmer field schools
• Train and visit
Duflo et al 2008, Blair et al. 2013, Kondylis et al. 2014, Beaman et al. 2015, Duflo and Suri, forthcoming
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
And yet, potentially big costs to
ignoring extension
• Upland Nerica Rice introduced in Sierra
Leone
• In Villages where seeds coupled with
extension, yields increased by 16%
• In villages where seeds were simply
distributed, yields fell
• Without extension, would be hard for farmers
to learn about yield potentialGlennerster and Suri, forthcoming
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Improving extension?
• Novelty is one difference between Nerica and some other extension services
• Nerica rice was brand new to upland Sierra Leone
• Extension similarly effective with newly developed orange-flesh sweet potato in Mozambique
• One plausible hypothesis: with new technologies, different technical cultivating characteristics, extension can be more effective
• Hard to test rigorously, though.
Hotz et al 2011, Glennerster and Suri forthcoming
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
How else to improve extension?
Contracting
Technology (ICT)
Last Mile: Social Diffusion
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Contracting: Incentive Structure
• Extension agents and contact farmers often face weak incentive environment
• Extension officers
• Incentives on other’s adoption have some effects
• Contact farmers
• Incentives based on own adoption (suggestive)
• Incentives based on other’s adoption lead to higher village adoption rates
• Monitoring? BenYishay and Mobarak 2013, Ben Yishay et al. 2015
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Incorporating Feedback
• User-driven curriculum a core element in FFS
• Feedback on extension may help
• Improves satisfaction & demand for extension services
• Improves knowledge in certain circumstances
• Less evidence of adoption/yield impacts
• Curriculum or Monitoring?Jones and Kondylis 2015, Masset and Haddad 2014
ICT to Reach Farmers Directly
• Interventions using mobile phones to
provide information to farmers have been
shown to increase adoption and improve
yields
Cole and Fernando 2012, Casaburi et al. 2014
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Mobile Phone-Based Agricultural Extension
• Gujarat, India
• 2011-2012
• Center for
Microfinance
• Awaaz.De
Cole and Fernando 2012
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Mobile Phone-Based Agricultural Extension
1200 cotton farmers
400 mobile extension
400 mobile extension and
traditional extension
400 comparison
Cole and Fernando 2012
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Mobile Phone-Based Agricultural Extension
• High take up and use of mobile platform
• Switch to more effective pesticides
• Increased adoption of cumin
• Some evidence of increased yields in
cotton and cumin
Cole and Fernando 2012, Cole and Fernando 2014
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
The Last Mile: Social Learning
• Most extension systems will not be able to
directly contact everybody
• Instead, most farmers will learn about a
new technology through social learning
• Can we take social learning for granted?
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Challenges to Social Learning: Targeting
• In 200 villages in Malawi
• Four different targeting rules to train two
people in a new planting practice
• In villages where the extension agent used
usual methods to choose the lead farmers
• Half showed no evidence of any social
learning.
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Beaman et al. 2015
Challenges to Social Learning: Targeting
• Does the targeting system get farmers
enough relevant information for social
learning to be effective?
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Social Learning in Villages
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Learning about Learning: Design
• Selection of partners so that the most people adopt if knowing one adopter is usually sufficient
Treatment 1: Simple Contagion
• Selection of partners to maximize adoption if most people need to know at least 2 adopters
Treatment 2: Complex Contagion
• Use geography as a proxy to full social network mapping
Treatment 3: Geography predicts
connections
• Business as usual: extension agent asks village head to nominate partners
Control
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
The Messenger Matters: Socialization
• A farmer is more likely to demand a new
technology if a greater proportion of
his/her network is demonstrating it
• For Pit Planting in Malawi: 70% of people
needed to see at least 2 connections to be
persuaded to adopt
Beaman et al. 2015, Tjernstrom 2015
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
The Messenger Matters: Socialization
• Farmers need intensive information for
really new, hard to adopt technologies
• Critical to train multiple people central to the
village network.
• A number of easy decision rules seem
not to do this
Beaman et al. 2015, Tjernstrom 2015
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
The Messenger Matters: Heterogeneity
• Lead farmers most closely resembling
target farmers were more effective at
promoting conservation agriculture
Beaman et al. 2015, Tjernstrom 2015
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
The Messenger Matters: Heterogeneity
• Heterogeneity in soil quality makes
farmers less likely to learn• Tjernstrom (2015) considers adoption of a new hybrid
maize seed variety in Kenya
• Considers the likelihood of adoption for trained and
untrained farmers as a function of underlying
heterogeneity
Beaman et al. 2015, Tjernstrom 2015
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Directly Trained Farmers
Tjernstrom 2015
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Heterogeneity Inhibits Learning
Tjernstrom 2015
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Can we find useful partners easily?
• Lead Farmers nominated by chief vs. peer farmers selected by focus groups
• Both only effective in the presence of additional high powered incentives
• Expensive (network mapping) effective without incentives
• Geography not very effective
• But, some hope:
• Informal elicitation of network position may be feasible Banerjee et al 2015, Beaman et al 2015, BenYishay and Mobarak 2013
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Summary: Information and Extension
• General extension is often ineffective, but
necessary
• Extension may be improved• Incentives
• Feedback
• Technology
• Leveraging social networks
• Do similar insights extend to other information
problems?• Recall novelty intuition: the message matters
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Price Information
• Prices vary substantially across markets, and across time in SSA
• If information constraints also prevent farmers from knowing current prevailing prices at different markets, farmers may be selling produce at suboptimal times and places
• Note that this learning problem is much simpler than for agricultural technology adoption…
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Provision of price information to
farmers is often ineffective
• May be because information is known
• More evidence of effectiveness in contexts
where search frictions are high
• Or because information is inactionable due
to bargaining power
• Some evidence: intermediaries are more able
to act on price information
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Aker 2010, Fafchamps and Minten 2012; Goyal 2010, Jensen 2007
Conclusions
• A lot of specific information is necessary for farmers to make informed decisions on technology adoption
• In this information needy context: higher adoption can be achieved through increasing the efficiency of information transfer
• Insights may not generalize to less information needy contexts, though
ConstraintsATAI
OverviewInformation
Agricultural Extension
Price Information
Conclusion
Recommended
