How do Farmers Learn from Extension Services

Transcription

1 How do Farmers Learn from Extension Services Evidence from Malawi A. Maertens, H. Michelson and V. Nourani Sussex, Illinois and Cornell UIUC April 3, 2018 A. Maertens, H. Michelson and V. Nourani (Sussex, IllinoisHow anddo Cornell) Farmers Learn from Extension Services UIUC April 3, / 13

2 Extension: A learning perspective Extension employs a range of models, e.g. training-and-visit, demonstration plots, and field days Returns to agricultural technologies are heterogeneous - depend on soil and climatic conditions farmers might be more likely to learn something useful about the profitability of a new technology when production context is known and similar to their own To maximize profit one needs to alter input use among many dimensions Learning about many dimensions might be cognitively demanding farmers might be more likely to learn about production processes if this learning is made easy and/or they want to learn A. Maertens, H. Michelson and V. Nourani (Sussex, IllinoisHow anddo Cornell) Farmers Learn from Extension Services UIUC April 3, / 13

3 This study Gain a better understanding of how farmers learn from extension services Establish the causal impact of demonstration plots versus field days on adoption Propose and test a learning model - rational inattention Combine (partial) Randomized Controlled Trial with panel data and qualitative insights Integrated Soil Fertility Management (ISFM) A. Maertens, H. Michelson and V. Nourani (Sussex, IllinoisHow anddo Cornell) Farmers Learn from Extension Services UIUC April 3, / 13

4 ISFM Set of technologies to preserve and build soil fertility, improve the use of nutrients and water, and increase yields Optimal planting practices, leguminous intercropping, organic and inorganic fertilizers, mulching, hybrid seeds Motivation Soil fertility in many parts of Sub-Saharan Africa is low and declining Yield benefits to ISFM can be substantial, albeit heterogenous Adoption remains uneven Research Question: How do demonstration plots and farmer field days impact farmer adoption of and knowledge of ISFM? A. Maertens, H. Michelson and V. Nourani (Sussex, IllinoisHow anddo Cornell) Farmers Learn from Extension Services UIUC April 3, / 13

5 Sample and randomization Implementing partner: Clinton Development Initiative (CDI) 2014: 250 villages in Central Malawi - Kasungu and Dowa districts divided randomly into treatment and control 125 treatment villages introduced to CDI s extension program and invited to form farmer clubs baseline survey among 2500 farmers farmer clubs invited to field days; 17 were selected (by CDI) for demonstration plots 2015: endline survey 1000 farmers A. Maertens, H. Michelson and V. Nourani (Sussex, IllinoisHow anddo Cornell) Farmers Learn from Extension Services UIUC April 3, / 13

6 CDI s extension program Pictures taken with permission of participants Maize, soy, groundnut and common beans demonstration plots A. Maertens, H. Michelson and V. Nourani (Sussex, IllinoisHow anddo Cornell) Farmers Learn from Extension Services UIUC April 3, / 13

7 Data collected Adoption and knowledge Adoption at base and endline: This year, on this plot, did you plant fertilizer trees and if so, which ones? Are you planning on cultivating soy this year? Aggregate: Use answers to generate an adoption score (out of 13) Also analyze the effects on adoption of specific promoted technologies Knowledge at endline: When mixing inoculant, how many tablespoons of sugar should you add to the inoculant bag? Which chemical is the best for controlling soya rust? Should the leaves of the fertiliser tree be exposed to the sun after harvesting? Aggregate: Use answers to generate a knowledge score (out of 20) Also analyze the effects on knowledge of particular techniques. Maertens, H. Michelson and V. Nourani (Sussex, IllinoisHow anddo Cornell) Farmers Learn from Extension Services UIUC April 3, / 13

8 Analysis and results Impact on adoption (cont.) At baseline, farmers on average report using 3.60 of the 13 promoted technologies Effects at endline Field day farmers: no effect. Farmers are equivalent to control farmers in planned adoption. Demo plot farmers report an intent to use 4.03 technologies; 12% increase over baseline. A. Maertens, H. Michelson and V. Nourani (Sussex, IllinoisHow anddo Cornell) Farmers Learn from Extension Services UIUC April 3, / 13

9 Analysis and results Impact on adoption (cont.) Strongest effects on soy inoculation and fertilizer trees, two knowledge-intensive technologies. Did demonstration plot participants simply learn more? A. Maertens, H. Michelson and V. Nourani (Sussex, IllinoisHow anddo Cornell) Farmers Learn from Extension Services UIUC April 3, / 13

10 Analysis and results Theory and tests Qualitative interviews: Field day participants report being impressed by the demonstrated technologies and yields, but acquire little new production knowledge report being unsure how the technologies and yields would translate on their own fields Demonstration plot participants formed beliefs about profitability and acquired production knowledge report information about the demo plot yields and what they thought this meant for their farm more likely to recall details: where to purchase and how to apply pesticides and innoculants A. Maertens, H. Michelson and V. Nourani (Sussex, IllinoisHow anddo Cornell) Farmers Learn from Extension Services UIUC April 3, / 13

11 Analysis and results Hypotheses about farmer learning Two-stage learning process First: form belief about usefulness of technology. Specifically, establish a belief about the profitability Only when this belief meets a particular cut-off, incur the cost to learn the production processes Implications Demonstration plot participants learn more Field day participants select what they learn A. Maertens, H. Michelson and V. Nourani (Sussex, IllinoisHow anddo Cornell) Farmers Learn from Extension Services UIUC April 3, / 13

12 Analysis and results Impact on farmer knowledge Expected mean score: (out of 20 questions) No effects on knowledge scores of field day farmers on average Demonstration plot farmer knowledge scores are 30% higher (10.58/20) Evidence of important differences in what farmers pay attention to in the context of a field day Field day farmers with credit constraints more likely to have knowledge of labor intensive technologies like plant spacing less likely to have knowledge of capital intensive technologies like urea use and fertilizer trees A. Maertens, H. Michelson and V. Nourani (Sussex, IllinoisHow anddo Cornell) Farmers Learn from Extension Services UIUC April 3, / 13

13 Implications for extension Constrained learning process Farmer field days could be matched with participants on the basis of growing conditions During farmer field days tools should be provided to farmers which will allow them to learn the information presented better. Examples: pamphlets/videos, measuring spoons, empty input bags. Re-coupling with credit/input interventions? Extension via cell phones would need to use simple language, be growing-condition specific and accompanied by (credit/input) market information Interested in learning about how current extension models facilitate learning; approaches and challenges A. Maertens, H. Michelson and V. Nourani (Sussex, IllinoisHow anddo Cornell) Farmers Learn from Extension Services UIUC April 3, / 13