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Lead-farmer extension and smallholder valuation of new agricultural technologies in Tanzania

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  • Morgan, Stephen N.
  • Mason, Nicole M.
  • Maredia, Mywish K.

Abstract

Encouraging the widespread adoption and use of new on-farm technologies is an important part of productivity-led strategies to promote agricultural transformation. While many interventions have been designed to promote adoption through extension and education, little is known about how these efforts influence farmer willingness-to-pay (WTP) for new technologies. We use a Becker-DeGroot-Marschak (BDM) mechanism to elicit farmer WTP for two improved seed varieties and a new seed treatment product, Apron Star, under two different lead-farmer extension treatments in Tanzania: (i) a demonstration plot showcasing the technologies within a village; and (ii) a demonstration plot coupled with distribution of trial packs enabling some farmers to test the technologies on their own land. In the BDM, farmers were presented with six products – the two bean varieties: without Apron Star, with Apron Star already applied, and with a sachet of Apron Star for the farmer to treat the seed him/herself. Our results suggest that neither extension treatment significantly affects WTP for these technologies. However, we find that farmers are willing to pay more for seed that is pre-treated with Apron Star than for seed bundled with a sachet of Apron Star for self-treatment.

Suggested Citation

  • Morgan, Stephen N. & Mason, Nicole M. & Maredia, Mywish K., 2020. "Lead-farmer extension and smallholder valuation of new agricultural technologies in Tanzania," Food Policy, Elsevier, vol. 97(C).
    • Handle: RePEc:eee:jfpoli:v:97:y:2020:i:c:s0306919220301597
    DOI: 10.1016/j.foodpol.2020.101955
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    as
    1. Yao Pan & Stephen C Smith & Munshi Sulaiman, 2018. "Agricultural Extension and Technology Adoption for Food Security: Evidence from Uganda," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(4), pages 1012-1031.
    2. repec:clg:wpaper:2013-20 is not listed on IDEAS
    3. Lori Beaman & Ariel BenYishay & Jeremy Magruder & Ahmed Mushfiq Mobarak, 2021. "Can Network Theory-Based Targeting Increase Technology Adoption?," American Economic Review, American Economic Association, vol. 111(6), pages 1918-1943, June.
    4. Whitfield, Stephen & Dixon, Jami L. & Mulenga, Brian P. & Ngoma, Hambulo, 2015. "Conceptualising farming systems for agricultural development research: Cases from Eastern and Southern Africa," Agricultural Systems, Elsevier, vol. 133(C), pages 54-62.
    5. Alberto Abadie & Susan Athey & Guido W Imbens & Jeffrey M Wooldridge, 2023. "When Should You Adjust Standard Errors for Clustering?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(1), pages 1-35.
    6. Mywish K. Maredia & Robert Shupp & Edward Opoku & Fulgence Mishili & Byron Reyes & Paul Kusolwa & Francis Kusi & Abdul Kudra, 2019. "Farmer perception and valuation of seed quality: Evidence from bean and cowpea seed auctions in Tanzania and Ghana," Agricultural Economics, International Association of Agricultural Economists, vol. 50(4), pages 495-507, July.
    7. Foster, Andrew D & Rosenzweig, Mark R, 1995. "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Journal of Political Economy, University of Chicago Press, vol. 103(6), pages 1176-1209, December.
    8. Oriana Bandiera & Imran Rasul, 2006. "Social Networks and Technology Adoption in Northern Mozambique," Economic Journal, Royal Economic Society, vol. 116(514), pages 869-902, October.
    9. Nakano, Yuko & Tsusaka, Takuji W. & Aida, Takeshi & Pede, Valerien O., 2018. "Is farmer-to-farmer extension effective? The impact of training on technology adoption and rice farming productivity in Tanzania," World Development, Elsevier, vol. 105(C), pages 336-351.
    10. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    11. Josephson, Anna Leigh & Ricker-Gilbert, Jacob & Florax, Raymond J.G.M., 2014. "How does population density influence agricultural intensification and productivity? Evidence from Ethiopia," Food Policy, Elsevier, vol. 48(C), pages 142-152.
    12. Masters, W.A. & Alvarez, G. Guevara, 2018. "Willingness to Pay for Hermetic Grain Storage Bags in Malawi," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277295, International Association of Agricultural Economists.
    13. Kondylis, Florence & Mueller, Valerie & Zhu, Jessica, 2017. "Seeing is believing? Evidence from an extension network experiment," Journal of Development Economics, Elsevier, vol. 125(C), pages 1-20.
    14. Simon Heß, 2017. "Randomization inference with Stata: A guide and software," Stata Journal, StataCorp LP, vol. 17(3), pages 630-651, September.
    15. Jenny C. Aker, 2011. "Dial “A” for agriculture: a review of information and communication technologies for agricultural extension in developing countries," Agricultural Economics, International Association of Agricultural Economists, vol. 42(6), pages 631-647, November.
    16. A. Colin Cameron & Douglas L. Miller, 2015. "A Practitioner’s Guide to Cluster-Robust Inference," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 317-372.
    17. Channa, Hira & Chen, Amy Z. & Pina, Patricia & Ricker-Gilbert, Jacob & Stein, Daniel, 2019. "What drives smallholder farmers’ willingness to pay for a new farm technology? Evidence from an experimental auction in Kenya," Food Policy, Elsevier, vol. 85(C), pages 64-71.
    18. Haroll Kokoye, Sãˆnakpon E. & Jolly, Curtis M. & Molnar, Joseph J. & Shannon, Dennis A. & Huluka, Gobena, 2018. "Farmer Willingness To Pay For Soil Testing Services In Northern Haiti," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 50(3), pages 429-451, August.
    19. Morawetz, Ulrich B. & De Groote, Hugo & Kimenju, Simon Chege, 2011. "Improving the Use of Experimental Auctions in Africa: Theory and Evidence," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 36(2), pages 1-17, August.
    20. Miriam Bruhn & David McKenzie, 2009. "In Pursuit of Balance: Randomization in Practice in Development Field Experiments," American Economic Journal: Applied Economics, American Economic Association, vol. 1(4), pages 200-232, October.
    21. Christopher B. Barrett & Luc Christiaensen & Megan Sheahan & Abebe Shimeles, 2017. "On the Structural Transformation of Rural Africa," Journal of African Economies, Centre for the Study of African Economies, vol. 26(suppl_1), pages 11-35.
    22. Munshi, Kaivan, 2004. "Social learning in a heterogeneous population: technology diffusion in the Indian Green Revolution," Journal of Development Economics, Elsevier, vol. 73(1), pages 185-213, February.
    23. Ricker-Gilbert, Jacob & Jumbe, Charles & Chamberlin, Jordan, 2014. "How does population density influence agricultural intensification and productivity? Evidence from Malawi," Food Policy, Elsevier, vol. 48(C), pages 114-128.
    24. Magnan, Nicholas & Spielman, David J. & Lybbert, Travis J. & Gulati, Kajal, 2015. "Leveling with friends: Social networks and Indian farmers' demand for a technology with heterogeneous benefits," Journal of Development Economics, Elsevier, vol. 116(C), pages 223-251.
    25. Ariel BenYishay & A Mushfiq Mobarak, 2019. "Social Learning and Incentives for Experimentation and Communication," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(3), pages 976-1009.
    26. My, Nguyen H.D. & Demont, Matty & Van Loo, Ellen J. & de Guia, Annalyn & Rutsaert, Pieter & Tuan, Tran Huu & Verbeke, Wim, 2018. "What is the value of sustainably-produced rice? Consumer evidence from experimental auctions in Vietnam," Food Policy, Elsevier, vol. 79(C), pages 283-296.
    27. Senakpon Kokoye & Joseph Molnar & Curtis Jolly & Dennis Shannon & Gobena Huluka, 2018. "Farmer knowledge and willingness to pay for soil testing in Haiti," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 45(7), pages 1109-1121, July.
    28. Timothy G. Conley & Christopher R. Udry, 2010. "Learning about a New Technology: Pineapple in Ghana," American Economic Review, American Economic Association, vol. 100(1), pages 35-69, March.
    29. Hugo De Groote & Simon Chege Kimenju & Ulrich B. Morawetz, 2011. "Estimating consumer willingness to pay for food quality with experimental auctions: the case of yellow versus fortified maize meal in Kenya," Agricultural Economics, International Association of Agricultural Economists, vol. 42(1), pages 1-16, January.
    30. Jenny C. Aker, 2011. "Dial “A” for Agriculture: A Review of Information and Communication Technologies for Agricultural Extension in Developing Countries - Working Paper 269," Working Papers 269, Center for Global Development.
    31. Kyle Emerick & Alain de Janvry & Elisabeth Sadoulet & Manzoor H. Dar, 2016. "Technological Innovations, Downside Risk, and the Modernization of Agriculture," American Economic Review, American Economic Association, vol. 106(6), pages 1537-1561, June.
    32. Matthew D. Webb, 2023. "Reworking wild bootstrap‐based inference for clustered errors," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 56(3), pages 839-858, August.
    33. Bensch, Gunther & Grimm, Michael & Peters, Jörg, 2015. "Why do households forego high returns from technology adoption? Evidence from improved cooking stoves in Burkina Faso," Journal of Economic Behavior & Organization, Elsevier, vol. 116(C), pages 187-205.
    34. Anderson, Jock R. & Feder, Gershon, 2007. "Agricultural Extension," Handbook of Agricultural Economics, in: Robert Evenson & Prabhu Pingali (ed.), Handbook of Agricultural Economics, edition 1, volume 3, chapter 44, pages 2343-2378, Elsevier.
    35. Moser, Christine M. & Barrett, Christopher B., 2003. "The disappointing adoption dynamics of a yield-increasing, low external-input technology: the case of SRI in Madagascar," Agricultural Systems, Elsevier, vol. 76(3), pages 1085-1100, June.
    36. Hoffmann, Vivian & Barrett, Christopher B. & Just, David R., 2009. "Do Free Goods Stick to Poor Households? Experimental Evidence on Insecticide Treated Bednets," World Development, Elsevier, vol. 37(3), pages 607-617, March.
    37. Waldman, Kurt B. & Kerr, John M. & Isaacs, Krista B., 2014. "Combining participatory crop trials and experimental auctions to estimate farmer preferences for improved common bean in Rwanda," Food Policy, Elsevier, vol. 46(C), pages 183-192.
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    Cited by:

    1. Maredia, Mywish K. & Farris, Jarrad G. & Mason, Nicole M. & Morgan, Stephen N., 2022. "Effectiveness of farmer-led extension that combines demonstration plots and free trial packs: A field experiment in Tanzania," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322528, Agricultural and Applied Economics Association.

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