The Impact on Farmer Incomes of a Nationwide Scaling Up of the Farmer Business School Program: Lessons and Insights from Central Malawi

Abstract

Various models and approaches are being implemented to provide technical assistance and support to improve smallholder farmers’ market access and incomes. This study evaluates the impact of the farmer business schools (FBS) program that has been scaled up to nationwide in Malawi. We focus on measuring impacts on crop choices and incomes of smallholder farmers, using the case study of Dedza district in central Malawi. The FBS approach, which has been implemented nationally by the Government of Malawi since 2011, consists of 1 year of group training and learning sessions for smallholder farmers. Training is designed to help improve market access and teach farmers how to establish profitable agribusiness ventures. This study used a multistage sampling procedure to collect data from 455 smallholder farmers: 162 FBS graduates, 84 FBS dropouts, and 209 nonparticipants. Using matching and difference-in-difference techniques, crop incomes from four groups of farmers were evaluated: FBS participants and FBS nonparticipants, as well as FBS graduates and FBS dropouts. The study finds a positive yet very small impact of FBS participation on crop income (US$20 per year on average), and no significant difference in crop income and production for farmers who graduated from FBS versus those who dropped out. While most participants reported gaining improved knowledge from the training, it did not seem to translate into new business ventures and improved incomes. Only a few graduates experienced improvement in income after FBS graduation. Insights from the qualitative research component of this study suggest that this is primarily due to the limited financial resources that smallholder farmers have to implement the agricultural management practices and business skills taught in FBS.

Resumen

Divers modèles et approches sont mis en œuvre pour fournir une assistance technique et un soutien visant à améliorer l’accès au marché et les revenus des petits exploitants agricoles. Cette étude évalue l’impact du programme d’écoles de commerce d’agriculteurs (FBS) qui a été étendu à l’ensemble du pays au Malawi. Nous nous concentrons sur la mesure de l’impact du programme sur le choix des cultures et sur les revenus des petits exploitants, en utilisant l’étude de cas du district de Dedza au centre du Malawi. L’approche du programme, mise en œuvre au niveau national par le gouvernement du Malawi depuis 2011, consiste en une année de formation collective et de sessions d’apprentissage pour les petits exploitants agricoles. La formation est conçue pour aider à améliorer l’accès au marché et à enseigner aux petits exploitants comment créer des entreprises agroalimentaires rentables. Cette étude a utilisé une procédure d’échantillonnage en plusieurs étapes pour collecter les données de 455 petits exploitants: 162 diplômés de la formation, 84 décrocheurs et 209 non participants. À l’aide de méthodes d’appariement et des différences de différences, les revenus des cultures de quatre groupes d’agriculteurs ont été évalués: les participants au programme et les non-participants, ainsi que les diplômés du programme et les décrocheurs. L’étude constate un impact positif mais très faible de la participation à la formation sur le revenu des cultures (20 USD par an en moyenne), et aucune différence significative au niveau du revenu et de la production des cultures entre les exploitants ayant obtenu leur diplôme de formation et ceux qui ont abandonné leurs études. Bien que la plupart des participants ait déclaré avoir amélioré leurs connaissances grâce à la formation, cela ne semblait pas se traduire par de nouvelles activités commerciales ni par une amélioration des revenus. Seuls quelques diplômés ont vu leurs revenus s’améliorer après l’obtention du diplôme de la formation. Les informations tirées du volet qualitatif de cette étude suggèrent que cela est principalement dû aux ressources financières dont disposent les petits exploitants agricoles, trop limitées pour mettre en œuvre les pratiques de gestion agricole et les compétences commerciales enseignées dans le cadre du programme.

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Fig. 1
Fig. 2

Notes

  1. 1.

    See Jayne and Rashid (2013) for a review of the evidence on the impacts of input subsidies in Africa; see Hanna and Karlan (2016) and Alderman et al. (2017) for a review of the evidence on transfers.

  2. 2.

    In a district, there are on average 80 to 90 AEDOs who operate in designated sections of the field. Currently, the ratio of extension workers to farmers in Dedza district is 1:3150.

  3. 3.

    Other measures of FBS program evaluation, including production quantity of promoted crops and sales, are presented in the appendices (Tables 7, 8, 9). Topics studied, as a proxy for knowledge gained by participants from the FBS program, are presented in “The Impact of FBS Participation” section.

  4. 4.

    Questions were open-ended and, as such, the responses came directly from participants.

  5. 5.

    See SNRD 2015, which showed promising results in terms of increasing productivity and farm incomes, although these results are self-reported by project teams without external validation and evaluation.

References

  1. Alderman, H., U. Gentilini, and R. Yemtsov, eds. 2017. The 1.5 Billion People Question: Food, Vouchers, or Cash Transfers? The World Bank. https://doi.org/10.1596/978-1-4648-1087-9.

  2. Barrett, C.B., M.E. Bachke, M.F. Bellemare, H.C. Michelson, S. Narayanan, and T.F. Walker. 2012. Smallholder Participation in Contract Farming: Comparative Evidence from Five Countries. World Development 40 (4): 715–730.

    Google Scholar 

  3. Berdegué, J. 2002. Learning to Beat Cochrane’s Treadmill: Public Policy, Markets and Social Learning in Chile’s Small-Scale Agriculture. In Wheelbarrows Full of Frogs: Social Learning in Rural Resource Management, ed. C. Leeuwis and R. Pyburn, 333–348. Assen, Netherlands: Koninklijke van Gorcum.

    Google Scholar 

  4. Birkhaeuser, D., R. Evenson, and G. Feder. 1991. The Economic Impact of Agricultural Extension: A Review. Economic Development and Cultural Change 39 (3): 607–650.

    Google Scholar 

  5. Birner R., K. Davis, J. Pender, E. Nkonya, P. Anandajayasekeram, J. Ekboir, A. Mbabu, D. Spielman, D. Horna, S. Benin, and M. Cohen. 2006. From Best Practice to Best Fit. A Framework for Analyzing Pluralistic Agricultural Advisory Services Worldwide. ISNAR Discussion Paper No. 5. Washington, DC: International Food Policy Research Institute.

  6. Braun, A., J. Jiggins, N. Röling, H. van den Berg, and P. Snijders. 2006. A Global Survey and Review of Farmer Field School Experiences. Report Prepared for the International Livestock Research Institute: Final Report, June 12. Wageningen, The Netherlands: International Livestock Research Institute. www.share4dev.info/kb/documents/1880.pdf.

  7. CARE USA. 2013. The Farmer Field and Business School. Innovation Brief. CARE Economic Development. https://www.care.org/sites/default/files/documents/AG-2013-FFBS-Pathways-Innovation-Brief.pdf. Accessed 20 May 2019.

  8. Cavatassi, R., M. González-Flores, P. Winters, J. Andrade-Piedra, P. Espinosa, and G. Thiele. 2011. Linking Smallholders to the New Agricultural Economy: The Case of the Plataformasde Concertaciónin Ecuador. Journal of Development Studies 47 (10): 1545–1573.

    Google Scholar 

  9. Chirwa, E. W., and M. Matita. 2012. From Subsistence to Smallholder Commercial Farming in Malawi: A Case of NASFAM Commercialisation Initiatives. Futures Agriculture Consortium (FAC) Working Paper 037. Brighton, UK: Futures Agricultural Consortium.

  10. Davis, K. 2006. Farmer Field Schools: A Boon or a Bust for Extension in Africa? Journal of International Agricultural and Extension Education 13: 91–97.

    Google Scholar 

  11. Davis, K., E. Nkonya, E. Kato, D. Mekonnen, M. Odendo, R. Miiro, and J. Nkuba. 2012. Impact of Farmer Field Schools on Agricultural Productivity and Poverty in East Africa. World Development 40 (2): 402–413.

    Google Scholar 

  12. DDA (Dedza District Assembly). 2001. Dedza District Socio-economic Profile. Dedza: Dedza District Assembly.

    Google Scholar 

  13. Devaux, A., J. Andrade-Piedra, D. Horton, M. Ordinola, G. Thiele, A. Thomann, and C. Velasco. 2010. Brokering Innovation for Sustainable Development: The Papa Andina Case. ILAC Working Paper 12. Rome, Italy: Institutional Learning and Change Initiative.

  14. Devaux, A., D. Horton, C. Velasco, G. Thiele, G. López, T. Bernet, I. Reinoso, and M. Ordinola. 2009. Collective Action for Market Chain Innovation in the Andes. Food Policy 34 (1): 31–38.

    Google Scholar 

  15. Devaux, A., M. Torero, J. Donovan, and D. Horton (eds.). 2016. Innovation for Inclusive Value-Chain Development: Successes and Challenges. Washington, DC: International Food Policy Research Institute.

    Google Scholar 

  16. Devaux, A., M. Torero, J. Donovan, and D. Horton. 2018. Agricultural Innovation and Inclusive Value-Chain Development: A Review. Journal of Agribusiness in Developing and Emerging Economies 8 (1): 99–123.

    Google Scholar 

  17. Ecker, O., K. Pauw, and I. Verduzco-Gallo. 2012. Did Malawi’s Food and Nutrition Security Really Improve? A Comparative Analysis of 2004/05 and 2010/11 Data. Report Prepared for Irish Aid, Malawi. Lilongwe, Malawi: International Food Policy Research Institute.

  18. FAO (Food and Agriculture Organization of the United Nations). 2011. Farm Business School Handbook: Training of Farmers Programme for South Asia. Bangkok, Thailand: FAO Corporate Document Repository, Regional Office for Asia and the Pacific.

    Google Scholar 

  19. Faure, G., K. Davis, C. Ragasa, S. Franzel, and S. Babu. 2016. Framework to Assess Performance and Impact of Pluralistic Agricultural Extension System. IFPRI Discussion Paper 01567. Washington, DC: International Food Policy Research Institute.

  20. Feder, G., J. Anderson, R. Birner, and K. Deininger. 2010. Promises and Realities of Community-Based Agricultural Extension. In Community, Market and State in Development, ed. K. Otsuka and K. Kalirajan, 187–208. London: Palgrave Macmillan.

    Google Scholar 

  21. Feder, G., R. Murgai, and J.B. Quizon. 2004. Sending Farmers Back to School: The Impact of Farmer Field Schools in Indonesia. Applied Economic Perspectives and Policy 26 (1): 45–62.

    Google Scholar 

  22. Friis-Hansen, E., and D. Duveskog. 2012. The Empowerment Route to Well-being: An Analysis of Farmer Field Schools in East Africa. World Development 40 (2): 414–427.

    Google Scholar 

  23. GIZ (Deutsche Gesellschaft für Internationale Zusammenarbeit). 2012. A Business Approach to Diversification Concepts and Experience of the FBS: An FBS Approach to Cocoa Farming. Bonn: GIZ.

    Google Scholar 

  24. Godtland, E.M., E. Sadoulet, A. Janvry, R. Murgai, and O. Ortiz. 2004. The Impact of Farmer-Field-Schools on Knowledge and Productivity: A Study of Potato Farmers in the Peruvian Andes. Economic Development and Cultural Change 53: 63–92.

    Google Scholar 

  25. GoM (Government of Malawi). 2011. Malawi Agricultural Sector Wide Approach: A Prioritised and Harmonised Agricultural Development Agenda: 2011–2015. Lilongwe, Malawi: Ministry of Agriculture, Irrigation and Water Development.

    Google Scholar 

  26. GoM (Government of Malawi). 2012. Guide to Agricultural Production and Natural Resources Management. Lilongwe, Malawi: Agricultural Communication Branch, Ministry of Agriculture, Irrigation and Water Development (MoAIWD).

    Google Scholar 

  27. Greene, W. 2011. Econometric Analysis, 7th ed. New York: Pearson.

    Google Scholar 

  28. Guo, M., X. Jia, J. Huang, K. Kumar, and N. Burger. 2015. Farmer Field School and Farmer Knowledge Acquisition in Rice Production: Experimental Evaluation in China. Agriculture, Ecosystems & Environment 209: 100–107.

    Google Scholar 

  29. Hanna, R., and D. Karlan. 2016. Designing Social Protection Programs: Using Theory and Experimentation to Understand How to Help Combat Poverty. Draft Paper. https://www.theigc.org/wp-content/uploads/2016/06/HannaKarlan_revision_v7.pdf. Accessed 20 May 2019.

  30. Hellin, J., M. Lundy, and M. Meijer. 2007. Farmer Organization, Collective Action and Market Access in Meso-America. CGIAR Systemwide Program on Collective Action and Property Rights (CAPRi), Working Paper 67. Washington, DC: International Food Policy Research Institute.

  31. Highfill, R., A. Moore, and P. McNamara. 2017. Malawi Youth in Agriculture (YIA) Project: Integrating Youth into Extension Systems in Central Malawi. Report for USAID, Feed the Future. Lilongwe, Malawi: USAID.

  32. Holden, S.T., M. Fisher, P.K. Samson, and C. Thierfelder. 2018. Can Lead Farmers Reveal the Adoption Potential of Conservation Agriculture? The Case of Malawi. Land Use Policy 76: 113–123. https://doi.org/10.1016/j.landusepol.2018.04.048.

    Article  Google Scholar 

  33. Imbens, G.W., and J.D. Angrist. 1994. Identification and Estimation of Local Average Treatment Effects. Econometrica 62: 467–476.

    Google Scholar 

  34. Jayne, T.S., and S. Rashid. 2013. Input Subsidy Programs in Sub-Saharan Africa: A Synthesis of Recent Evidence. Agricultural Economics 44 (6): 547–562.

    Google Scholar 

  35. Kariyasa, K., and A. Dewi. 2011. Analysis of Factors Affecting Adoption of Integrated Crop Management Farmer Field School (ICM-FFS) in Swampy Areas. International Journal of Food and Agricultural Economics 1 (2): 29–38.

    Google Scholar 

  36. Khandker, S., B. Koolwal, and H. Samad. 2009. Handbook on Impact Evaluation: Quantitative Methods and Practices. Washington, DC: The World Bank.

    Google Scholar 

  37. Kondylis, F., V. Mueller, and J. Zhu. 2017. Seeing is Believing? Evidence from an Extension Network Experiment. Journal of Development Economics 125: 1–20. https://doi.org/10.1016/j.jdeveco.2016.10.004.

    Article  Google Scholar 

  38. Krishnan, P., and M. Patnam. 2014. Neighbors and Extension Agents in Ethiopia: Who Matters More for Technology Adoption? American Journal of Agricultural Economics 96 (1): 308–327. https://doi.org/10.1093/ajae/aat017.

    Article  Google Scholar 

  39. Larsen, A., and H.B. Lilleør. 2014. Beyond the Field: The Impact of Farmer Field Schools on Food Security and Poverty Alleviation. World Development 64: 843–859.

    Google Scholar 

  40. Lyon, S., T. Mutersbaugh, and H. Worthen. 2017. The Triple Burden: The Impact of Time Poverty on Women’s Participation in Coffee Producer Organizational Governance in Mexico. Agriculture and Human Values 34 (2): 317–331.

    Google Scholar 

  41. Maertens, M., L. Colen, and J.F.M. Swinnen. 2011. Globalisation and Poverty in Senegal: A Worst Case Scenario? European Review of Agricultural Economics 38 (1): 31–54.

    Google Scholar 

  42. Maertens, M., and J.F.M. Swinnen. 2009. Trade, Standards, and Poverty: Evidence from Senegal. World Development 37 (1): 161–178.

    Google Scholar 

  43. Maertens, M., and J.F.M. Swinnen. 2012. Gender and Modern Supply Chains in Developing Countries. Journal of Development Studies 48 (10): 1412–1430.

    Google Scholar 

  44. Maonga, B.B., A.M. Maganga, and E.M.K. Haraman. 2013. Adoption of Small Metallic Grain Silos in Malawi: A Farm Level Cross-Sectional Study. International Journal of Development and Sustainability 2 (2): 1534–1548.

    Google Scholar 

  45. Maonga, B.B., A.M. Maganga, and H. Kankwamba. 2015. Smallholder Farmers Willingness to Incorporate Biofuel Crops into Cropping Systems in Malawi. International Journal of Food and Agricultural Economics 3 (1): 87–100.

    Google Scholar 

  46. Mayoux, L. 2012. Gender Mainstreaming in Value Chain Development: Experience with Gender Action Learning System in Uganda. Enterprise Development and Microfinance. https://doi.org/10.3362/1755-1986.2012.031.

    Article  Google Scholar 

  47. Mazunda, J., H. Kankwamba, and K. Pauw. 2014. Food and Nutrition Security Implications of Crop Diversification in Malawi’s Farm Households. In Mapping the Linkages Between Agriculture, Food Security and Nutrition in Malawi, ed. N.L. Aberman, J. Meerman, and T. Benson, 44–49. Lilongwe, Malawi and Washington DC: International Food Policy Research Institute.

    Google Scholar 

  48. Mulema, A. A. 2012. Organization of Innovation Platforms for Agricultural Research and Development in the Great Lakes Region of Africa. Graduate theses and dissertations, Paper 12631. Iowa State University, USA.

  49. Niu, C., and C. Ragasa. 2018. Selective Attention and Information Loss in the Lab-to-Farm Knowledge Chain: The Case of Malawian Agricultural Extension Programs. Agricultural Systems 165: 147–163.

    Google Scholar 

  50. NSO (National Statistical Office). 2012. Integrated Household Survey 2010/2011: Household Socio-economic Characteristics Report. Zomba: National Statistical Office.

    Google Scholar 

  51. Pamuk, H., E. Bulte, and A. Adekunle. 2014. Do Decentralized Innovation Systems Promote Agricultural Technology Adoption? Experimental Evidence from Africa. Food Policy 44: 227–236.

    Google Scholar 

  52. Poole, N., M. Chitundu, and R. Msoni. 2013. Commercialisation: A Meta-approach for Agricultural Development Among Smallholder Farmers in Africa? Food Policy 41: 155–165.

    Google Scholar 

  53. Quizon, J., G. Feder, and R. Murgai. 2001. Fiscal Sustainability of Agricultural Extension: The Case of the Farmer Field School Approach. Journal of International Agricultural and Extension Education 8 (1): 13.

    Google Scholar 

  54. Ragasa, C. 2019. Modelling the Effectiveness of the Lead Farmer Approach in Agricultural Extension Service: Nationally Representative Panel Data Analysis in Malawi. Malawi: International Food Policy Research Institute. http://massp.ifpri.info/2019/03/06/modeling-the-effectiveness-of-the-lead-farmer-approach-in-agricultural-extension-service-nationally-representative-panel-data-analysis-in-malawi/. Accessed 6 Mar 2019.

  55. Ragasa, C., T. Badibanga, and J. Ulimwengu. 2016. Effectiveness and Challenges of Participatory Governance: The Case of Agricultural and Rural Management Councils in the Western Democratic Republic of the Congo. Food Security 8: 827–854.

    Google Scholar 

  56. Ragasa, C., I. Lambrecht, and D. Kufoalor. 2018. Limitations of Contract Farming as a Pro-poor Strategy: The Case of Maize Outgrower Schemes in Upper West Ghana. World Development 102: 30–56.

    Google Scholar 

  57. Ragasa, C., and J. Mazunda. 2018. The Impact of Agricultural Extension Services in the Context of a Heavily Subsidized Input System: The Case of Malawi. World Development 105: 25–47.

    Google Scholar 

  58. Ragasa, C., D. Mzungu, E. Kaima, C. Kazembe, and K. Kalagho. 2017. “Capacity and Accountability in the Agricultural Extension System in Malawi: Insights From the Survey of Service Providers in 15 Districts.” IFPRI Discussion Paper 01673. Washington, DC: International Food Policy Research Institute.

  59. Reardon, T., D. Boughton, D. Tschirley, S. Haggblade, M. Dolislager, B. Minten, and R. Hernandez. 2015. Urbanization, Diet Change, and Transformation of the Downstream and Midstream of the Agrifood System: Effects on the Poor in Africa and Asia. Faith & Economics 66: 43–63.

    Google Scholar 

  60. Riisgaard, L., S. Bolwig, F. Matose, S. Ponte, A. du Toit, and N. Halberg. 2008. A Strategic Framework and Toolbox for Action Reserach with Small Producers in Value Chains. DIIS Working Paper 17. Denmark: Danish Institute for International Studies.

  61. Riisgaard, L., S. Bolwig, S. Ponte, A. du Toit, N. Halberg, and F. Matose. 2010. Integrating Poverty and Environmental Concerns into Value-Chain Analysis: A Strategic Framework and Practical Guide. Development Policy Review 28 (2): 173–194.

    Google Scholar 

  62. Rosenbaum, P.R., and D. Rubin. 1983. The Central Role of the Propensity Score in Observational Studies for Causal Effects. Biometrika 70 (1): 41–55.

    Google Scholar 

  63. Rubin, D. 1978. Bayesian Inference for Causal Effects: The Role of Randomization. Annals of Statistics 6 (1): 34–58.

    Google Scholar 

  64. Sanginga, P., R. Best, C. Chitsike, R. Delve, S. Kaaria, and R. Kirkby. 2004. Linking Smallholder Farmers to Markets in East Africa. Mountain Research and Development 24 (4): 288–291.

    Google Scholar 

  65. Schut, M., L. Klerkx, M. Sartas, D. Lamers, M. Campbell, I. Ogbonna, P. Kaushik, K. Atta-Krah, and C. Leeuwis. 2016. Innovation Platforms: Experiences with Their Institutional Embedding in Agricultural Research for Development. Experimental Agriculture 52 (4): 537–561. https://doi.org/10.1017/S001447971500023X.

    Article  Google Scholar 

  66. Sinyolo, S., and M. Mudhara. 2018. The Impact of Enterpreneurial Competencies on Household Food Security Among Smallholder Farmers in Kwazulu Natal, South Africa. Ecology of Food and Nutrition 57 (2): 71–93.

    Google Scholar 

  67. Smith, J.A., and P. Todd. 2005. Does Matching Overcome Lalonde’s Critique of Nonexperimental Estimators? Journal of Econometrics 125 (1–2): 305–353.

    Google Scholar 

  68. SNRD (Sector Network Rural Development Africa). 2015. Experiences with the Farmer Business School (FBS) Approach in Africa. Bonn: GIZ.

    Google Scholar 

  69. Todd, P.E. 2007. Chapter 60 Evaluating Social Programs with Endogenous Program Placement and Selection of the Treated. In Handbook of Development Economics, vol. 4, ed. T.P. Schultz and J.A. Strauss, 3847–3894. Amsterdam, The Netherlands: North Holland.

    Google Scholar 

  70. Todo, Y., and R. Takashi. 2011. Impact of Farmer Field Schools on Agricultural Income and Skills: Evidence from an Aid-Funded Project in Rural Ethiopia. Journal of International Development 25 (3): 362–381.

    Google Scholar 

  71. Uaiene, R., C. Arndt, and W. Masters. 2009. Determinants of Agricultural Technology Adoption in Mozambique. Discussion Paper No. 67E. Mozambique: National Directorate of Studies and Policy Analysis, Ministry of Planning and Development.

  72. van den Berg, H. 2004. IPM Farmer Field Schools: A Synthesis of 25 Impact Evaluations. Report prepared for the Global IPM Facility, Wageningen University, Wageningen, The Netherlands.

  73. van den Berg, H., and J. Jiggins. 2007. Investing in Farmers—The Impacts of Farmer Field Schools in Relation to Integrated Pest Management. World Development 35 (4): 663–686.

    Google Scholar 

  74. Van den Broeck, G., K. Van Hoyweghen, and M. Maertens. 2018. Horticultural Exports and Food Security in Senegal. Global Food Security 17 (June): 162–171.

    Google Scholar 

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Acknowledgement

The authors are grateful for the funding provided by Government of Flanders (Grant No. 602134.002.001). Joanna Chilemba extends her gratitude to the African Economic Research Consortium (AERC); the IFPRI Malawi Country Strategy Support Program Bunda Grant Scheme mentorship program, and professors at LUANAR: Professor Davis H. Ng’ong’ola, Professor Charles Jumbe, and Mr. Assa M. Maganga.

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Appendix

Appendix

See Tables 7, 8, 9, 10, 11 and Figs. 3, 4.

Table 7 ATT on average total crop production (kg)
Table 8 ATT on average value of crops sold (MWK)
Table 9 ATT on average value of crop production (MWK)
Table 10 Quality of matching
Table 11 Units of measurement of explanatory variables, and expected effects on FBS participation
Fig. 3
figure3

Overall participant satisfaction with facilitation and implementation of FBS

Fig. 4
figure4

Topics studied by FBS participants

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Chilemba, J., Ragasa, C. The Impact on Farmer Incomes of a Nationwide Scaling Up of the Farmer Business School Program: Lessons and Insights from Central Malawi. Eur J Dev Res 32, 906–938 (2020). https://doi.org/10.1057/s41287-019-00246-y

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Keywords

  • Farmer business schools
  • Extension services
  • Market access
  • Impact evaluation
  • Income generation
  • Malawi