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Measuring agricultural knowledge and adoption

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  • Florence Kondylis
  • Valerie Mueller
  • S. Zhu

Abstract

Understanding the tradeoffs in improving the precision of agricultural measures through survey design is crucial. Yet, standard indicators used to determine program effectiveness may be flawed, and at a differential rate for men and women. We use a household survey from Mozambique to estimate the measurement error from male and female self-reports of their adoption and knowledge of three practices: intercropping, mulching, and strip tillage. Despite clear differences in human and physical capital, there are no obvious differences in the knowledge, adoption, and error in self-reporting between men and women. Having received training unanimously lowers knowledge misreports and increases adoption misreports. Other determinants of reporting error differ by gender. Misreporting is positively associated with a greater number of plots for men. Recall decay on measures of knowledge appears prominent among men but not women. Findings from regression and cost-effectiveness analyses always favor the collection of objective measures of knowledge. Given the lowest rate of accuracy for adoption was around 80%, costlier objective adoption measures are recommended for a subsample in regions with heterogeneous farm sizes.

Suggested Citation

  • Florence Kondylis & Valerie Mueller & S. Zhu, 2015. "Measuring agricultural knowledge and adoption," Agricultural Economics, International Association of Agricultural Economists, vol. 46(3), pages 449-462, May.
    • Handle: RePEc:bla:agecon:v:46:y:2015:i:3:p:449-462
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    2. 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.
    3. Denise Hörner & Adrien Bouguen & Markus Frölich & Meike Wollni, 2019. "The Effects of Decentralized and Video-based Extension on the Adoption of Integrated Soil Fertility Management – Experimental Evidence from Ethiopia," NBER Working Papers 26052, National Bureau of Economic Research, Inc.
    4. Alix-Garcia, Jennifer M. & Sims, Katharine R.E. & Costica, Laura, 2021. "Better to be indirect? Testing the accuracy and cost-savings of indirect surveys," World Development, Elsevier, vol. 142(C).
    5. Tewodaj Mogues & Valerie Mueller & Florence Kondylis, 2019. "Cost-effectiveness of community-based gendered advisory services to farmers: Analysis in Mozambique and Tanzania," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-32, March.
    6. Khushbu Mishra & Abdoul G. Sam & Gracious M. Diiro & Mario J. Miranda, 2020. "Gender and the dynamics of technology adoption: Empirical evidence from a household‐level panel data," Agricultural Economics, International Association of Agricultural Economists, vol. 51(6), pages 857-870, November.
    7. Annemie Maertens & Hope Michelson & Vesall Nourani, 2021. "How Do Farmers Learn from Extension Services? Evidence from Malawi," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(2), pages 569-595, March.
    8. Okello, Julius & Shikuku, Kelvin Mashisia & Lagerkvist, Carl Johan & Rommel, Jens & Jogo, Wellington & Ojwang, Sylvester & Namanda, Sam & Elungat, James, 2023. "Social incentives as nudges for agricultural knowledge diffusion and willingness to pay for certified seeds: Experimental evidence from Uganda," Food Policy, Elsevier, vol. 120(C).
    9. Rachid Laaja & Karen Macours, 2021. "Measuring Skills in Developing Countries," Journal of Human Resources, University of Wisconsin Press, vol. 56(4), pages 1254-1295.
    10. Shikuku, K.M., 2018. "Information exchange links, knowledge exposure, and adoption of agricultural technologies in Northern Uganda," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 275974, International Association of Agricultural Economists.

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