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Impact of farmer field schools on agricultural productivity and poverty in East Africa

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  • Davis, Kristin
  • Nkonya, Ephraim
  • Kato, Edward
  • Mekonnen, Daniel Ayalew
  • Odendo, Martins
  • Miiro, Richard
  • Nkuba, Jackson

Abstract

Farmer field schools (FFSs) are a popular education and extension approach worldwide. Such schools use experiential learning and a group approach to facilitate farmers in making decisions, solving problems, and learning new techniques. However, there is limited or conflicting evidence as to their effect on productivity and poverty, especially in East Africa. This study is unique in that it uses a longitudinal impact evaluation (difference in difference approach) with quasi-experimental methods (propensity score matching and covariate matching) together with qualitative approaches to provide rigorous evidence to policymakers and other stakeholders on an FFS project in Kenya, Tanzania, and Uganda. The study provides evidence on participation in FFSs and on the effects of FFSs on various outcomes. The study found that younger farmers who belong to other groups, such as savings and credit groups, tended to participate in field schools. Females made up 50 percent of FFS membership. Reasons for not joining an FFS included lack of time and information. FFSs were shown to be especially beneficial to women, people with low literacy levels, and farmers with medium-size land holdings. FFS participants had significant differences in outcomes with respect to value of crops produced per acre, livestock value gain per capita, and agricultural income per capita. FFSs had a greater impact on crop productivity for those in the middle land area (land poverty) tercile. Participation in FFSs increased income by 61 percent when pooling the three countries. FFSs improved income and productivity overall, but differences were seen at the country level. Participation in FFSs led to increased production, productivity, and income in nearly all cases: Kenya, Tanzania, and at the project level (all three countries combined). The most significant change was seen in Kenya for crops (80 percent increase) and in Tanzania for agricultural income (more than 100 percent increase). A lack of significant increases in Uganda was likely due to Uganda’s National Agricultural Advisory Services. When disaggregating by gender, however, female-headed households benefited significantly more than male-headed households in Uganda.

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Bibliographic Info

Paper provided by International Food Policy Research Institute (IFPRI) in its series IFPRI discussion papers with number 992.

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Date of creation: 2010
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Handle: RePEc:fpr:ifprid:992

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Keywords: farmer field schools; agricultural productivity; adoption; extension services;

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References

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Citations

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Cited by:
  1. Meinzen-Dick, Ruth & Quisumbing, Agnes & Behrman, Julia & Biermayr-Jenzano, Patricia & Wilde, Vicki & Noordeloos, Marco & Ragasa, Catherine & Beintema, Nienke, 2010. "Engendering agricultural research," IFPRI discussion papers 973, International Food Policy Research Institute (IFPRI).
  2. Peterman, Amber & Behrman, Julia & Quisumbing, Agnes, 2010. "A review of empirical evidence on gender differences in nonland agricultural inputs, technology, and services in developing countries," IFPRI discussion papers 975, International Food Policy Research Institute (IFPRI).
  3. Humphries, Sally & Classen, Lauren & Jiménez, José & Sierra, Fredy & Gallardo, Omar & Gómez, Marvin, 2012. "Opening Cracks for the Transgression of Social Boundaries: An Evaluation of the Gender Impacts of Farmer Research Teams in Honduras," World Development, Elsevier, vol. 40(10), pages 2078-2095.
  4. Tambo, Justice A. & Wünscher, Tobias, 2014. "Building farmers’ capacity for innovation generation: what are the determining factors?," 88th Annual Conference, April 9-11, 2014, AgroParisTech, Paris, France 170351, Agricultural Economics Society.
  5. Carlberg, Eric & Kostandini, Genti & Dankyi, Awere, 2012. "The Effects of Integrated Pest Management Techniques (IPM) Farmer Field Schools on Groundnut Productivity: Evidence from Ghana," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124876, Agricultural and Applied Economics Association.
  6. Brooks, Karen & Zorya, Sergiy & Gautam, Amy & Goyal, Aparajita, 2013. "Agriculture as a sector of opportunity for young people in Africa," Policy Research Working Paper Series 6473, The World Bank.
  7. Wielgosz, Benjamin & Mangheni, Margaret Najjingo & Tsegai, Daniel & Ringler, Claudia, 2012. "Malaria and agriculture: A global review of the literature with a focus on the application of integrated pest and vector management in East Africa and Uganda," IFPRI discussion papers 1232, International Food Policy Research Institute (IFPRI).
  8. Glendenning, Claire J. & Babu, Suresh & Asenso-Okyere, Kwadwo, 2010. "Review of agricultural extension in India: Are farmers' information needs being met?," IFPRI discussion papers 1048, International Food Policy Research Institute (IFPRI).
  9. Kangogo, Daniel & Lagat, Job & Ithinji, Gicuru, 2013. "The Influence of Social Capital Dimensions on Household Participation in Micro-Credit Groups and Loan Repayment Performance in Uasin Gishu County, Kenya," MPRA Paper 48624, University Library of Munich, Germany.
  10. Minten, Bart & Koro, Bethlehem & Stifel, David, 2013. "The last mile(s) in modern input distribution: Evidence from Northwestern Ethiopia," ESSP working papers 51, International Food Policy Research Institute (IFPRI).
  11. Friis-Hansen, Esbern & Duveskog, Deborah, 2012. "The Empowerment Route to Well-being: An Analysis of Farmer Field Schools in East Africa," World Development, Elsevier, vol. 40(2), pages 414-427.
  12. B. Bala & S. Majumder & S. Altaf Hossain & M. Haque & M. Hossain, 2013. "Exploring development strategies of agricultural systems of Hill Tracts of Chittagong in Bangladesh," Environment, Development and Sustainability, Springer, vol. 15(4), pages 949-966, August.
  13. Croppenstedt, Andre & Goldstein, Markus & Rosas, Nina, 2013. "Gender and agriculture : inefficiencies, segregation, and low productivity traps," Policy Research Working Paper Series 6370, The World Bank.
  14. Adong, Annet & Mwaura, Francis & Okoboi, Geofrey, 2012. "What factors determine membership to farmer groups in Uganda? Evidence from the Uganda Census of Agriculture 2008/9," Research Series 148950, Economic Policy Research Centre (EPRC).
  15. Muhammad Khan & Muhammad Khan & Khalid Zaman & Muhammad Khan, 2014. "The evolving role of agricultural technology indicators and economic growth in rural poverty: has the ideas machine broken down?," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(4), pages 2007-2022, July.

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