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Estimating the Direct and Indirect Effects of Improved Seed Adoption on Yields: Evidence from DNA-Fingerprinting, Crop cuts, and Self-Reporting in Ethiopia

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  • Jovanovic, Nina
  • Ricker-Gilbert, Jacob

Abstract

Farmer adoption of improved crop varieties can potentially increase yields and enhance household welfare in the developing world. However, the presence of measurement errors in household surveys poses a serious challenge to estimating the true returns to adopting improved varieties. This article analyzed the impacts of three sources of measurement error caused by farmers’ misperceptions of the varieties they planted, the area they planted, and the quantities they harvested, on maize yields and input use, using the 2018/19 Ethiopia Socio-economic Survey. These data included DNA-fingerprinting of seed, GPS plot size information, and crop cuts that we compared to farmers’ self-reported estimates of these measures. Doing so allowed us to determine the degree of measurement error in the estimates of improved maize adoption. Results indicated that the measurement error in self-reported adoption of improved maize varieties attenuated their estimated yield gains by 12 percentage points on average. Furthermore, we used the relationship between self-reported and DNA-fingerprinted adoption to disaggregate how much of the yield gains from improved seeds was due to better seed genetics and how much was due to increased effort by the farmers who planted them. We found that improved seed genetics accounted for a 22 percentage point yield increase over traditional seed, and observable effort through increased input use accounted for a 15 percentage point gain for improved varieties on average. Understanding these effects has important implications for justifying the continued funding of development of improved seed varieties and their dissemination to smallholder farmers.

Suggested Citation

  • Jovanovic, Nina & Ricker-Gilbert, Jacob, 2023. "Estimating the Direct and Indirect Effects of Improved Seed Adoption on Yields: Evidence from DNA-Fingerprinting, Crop cuts, and Self-Reporting in Ethiopia," 2023 Seventh AAAE/60th AEASA Conference, September 18-21, 2023, Durban, South Africa 365985, African Association of Agricultural Economists (AAAE).
  • Handle: RePEc:ags:aaae23:365985
    DOI: 10.22004/ag.econ.365985
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    1. Andrew Dillon & Sydney Gourlay & Kevin McGee & Gbemisola Oseni, 2019. "Land Measurement Bias and Its Empirical Implications: Evidence from a Validation Exercise," Economic Development and Cultural Change, University of Chicago Press, vol. 67(3), pages 595-624.
    2. Gourlay, Sydney & Kilic, Talip & Lobell, David B., 2019. "A new spin on an old debate: Errors in farmer-reported production and their implications for inverse scale - Productivity relationship in Uganda," Journal of Development Economics, Elsevier, vol. 141(C).
    3. Calogero Carletto & Sydney Gourlay & Paul Winters, 2015. "Editor's choice From Guesstimates to GPStimates: Land Area Measurement and Implications for Agricultural Analysis," Journal of African Economies, Centre for the Study of African Economies, vol. 24(5), pages 593-628.
    4. 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.
    5. Gashaw Tadesse Abate & Tanguy Bernard & Alan de Brauw & Nicholas Minot, 2018. "The impact of the use of new technologies on farmers’ wheat yield in Ethiopia: evidence from a randomized control trial," Agricultural Economics, International Association of Agricultural Economists, vol. 49(4), pages 409-421, July.
    6. Kibrom A. Abay & Leah E. M. Bevis & Christopher B. Barrett, 2021. "Measurement Error Mechanisms Matter: Agricultural Intensification with Farmer Misperceptions and Misreporting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(2), pages 498-522, March.
    7. Kibrom A. Abay & Tesfamicheal Wossen & Jordan Chamberlin, 2023. "Mismeasurement and efficiency estimates: Evidence from smallholder survey data in Africa," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 413-434, June.
    8. Tahirou Abdoulaye & Tesfamicheal Wossen & Bola Awotide, 2018. "Impacts of improved maize varieties in Nigeria: ex-post assessment of productivity and welfare outcomes," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(2), pages 369-379, April.
    9. Di Zeng & Jeffrey Alwang & George W. Norton & Bekele Shiferaw & Moti Jaleta & Chilot Yirga, 2015. "Ex post impacts of improved maize varieties on poverty in rural Ethiopia," Agricultural Economics, International Association of Agricultural Economists, vol. 46(4), pages 515-526, July.
    10. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843, Elsevier.
    11. Francis Addeah Darko & Amparo Palacios-Lopez & Talip Kilic & Jacob Ricker-Gilbert, 2018. "Micro-Level Welfare Impacts of Agricultural Productivity: Evidence from Rural Malawi," Journal of Development Studies, Taylor & Francis Journals, vol. 54(5), pages 915-932, May.
    12. Lori Beaman & Dean Karlan & Bram Thuysbaert & Christopher Udry, 2013. "Profitability of Fertilizer: Experimental Evidence from Female Rice Farmers in Mali," American Economic Review, American Economic Association, vol. 103(3), pages 381-386, May.
    13. Ayala Wineman & Timothy Njagi & C. Leigh Anderson & Travis W. Reynolds & Didier Yélognissè Alia & Priscilla Wainaina & Eric Njue & Pierre Biscaye & Miltone W. Ayieko, 2020. "A Case of Mistaken Identity? Measuring Rates of Improved Seed Adoption in Tanzania Using DNA Fingerprinting," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(3), pages 719-741, September.
    14. Desiere, Sam & Jolliffe, Dean, 2018. "Land productivity and plot size: Is measurement error driving the inverse relationship?," Journal of Development Economics, Elsevier, vol. 130(C), pages 84-98.
    15. Tavneet Suri, 2011. "Selection and Comparative Advantage in Technology Adoption," Econometrica, Econometric Society, vol. 79(1), pages 159-209, January.
    16. Julius Manda & Arega D. Alene & Adane H. Tufa & Tahirou Abdoulaye & Alpha Y. Kamara & Olusoji Olufajo & Ousmane Boukar & Victor M. Manyong, 2020. "Adoption and Ex‐post Impacts of Improved Cowpea Varieties on Productivity and Net Returns in Nigeria," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(1), pages 165-183, February.
    17. Khonje, Makaiko G. & Nyondo, Christone & Mangisoni, Julius H. & Ricker-Gilbert, Jacob & Burke, William J. & Chadza, William & Muyanga, Milu, 2022. "Does subsidizing legume seeds improve farm productivity and nutrition in Malawi?," Food Policy, Elsevier, vol. 113(C).
    18. Carletto, Calogero & Savastano, Sara & Zezza, Alberto, 2013. "Fact or artifact: The impact of measurement errors on the farm size–productivity relationship," Journal of Development Economics, Elsevier, vol. 103(C), pages 254-261.
    19. Jeffrey D Michler & Emilia Tjernström & Simone Verkaart & Kai Mausch, 2019. "Money Matters: The Role of Yields and Profits in Agricultural Technology Adoption," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(3), pages 710-731.
    20. David B Lobell & George Azzari & Marshall Burke & Sydney Gourlay & Zhenong Jin & Talip Kilic & Siobhan Murray, 2020. "Eyes in the Sky, Boots on the Ground: Assessing Satellite‐ and Ground‐Based Approaches to Crop Yield Measurement and Analysis," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(1), pages 202-219, January.
    21. Morris, Michael L. & Risopoulos, Jean & Beck, David, 1999. "Genetic Change in Farmer-Recycled Maize Seed: A Review of the Evidence," Economics Working Papers 7683, CIMMYT: International Maize and Wheat Improvement Center.
    22. Moti Jaleta & Menale Kassie & Paswel Marenya & Chilot Yirga & Olaf Erenstein, 2018. "Impact of improved maize adoption on household food security of maize producing smallholder farmers in Ethiopia," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(1), pages 81-93, February.
    23. Bezu, Sosina & Kassie, Girma T. & Shiferaw, Bekele & Ricker-Gilbert, Jacob, 2014. "Impact of Improved Maize Adoption on Welfare of Farm Households in Malawi: A Panel Data Analysis," World Development, Elsevier, vol. 59(C), pages 120-131.
    24. Wossen, Tesfamicheal & Abay, Kibrom A. & Abdoulaye, Tahirou, 2022. "Misperceiving and misreporting input quality: Implications for input use and productivity," Journal of Development Economics, Elsevier, vol. 157(C).
    25. Rachid Laajaj & Karen Macours & Cargele Masso & Moses Thuita & Bernard Vanlauwe, 2020. "Reconciling yield gains in agronomic trials with returns under African smallholder conditions," PSE-Ecole d'économie de Paris (Postprint) halshs-02973685, HAL.
    26. Yacoubou Djima,Ismael & Kilic,Talip, 2021. "Survey Measurement Errors and the Assessment of the Relationship between Yields and Inputs inSmallholder Farming Systems : Evidence from Mali," Policy Research Working Paper Series 9841, The World Bank.
    27. Erwin Bulte & Gonne Beekman & Salvatore Di Falco & Joseph Hella & Pan Lei, 2014. "Behavioral Responses and the Impact of New Agricultural Technologies: Evidence from a Double-blind Field Experiment in Tanzania," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(3), pages 813-830.
    28. Di Zeng & Jeffrey Alwang & George W. Norton & Bekele Shiferaw & Moti Jaleta & Chilot Yirga, 2017. "Agricultural technology adoption and child nutrition enhancement: improved maize varieties in rural Ethiopia," Agricultural Economics, International Association of Agricultural Economists, vol. 48(5), pages 573-586, September.
    29. Tesfamicheal Wossen & Tahirou Abdoulaye & Arega Alene & Pierre Nguimkeu & Shiferaw Feleke & Ismail Y Rabbi & Mekbib G Haile & Victor Manyong, 2019. "Estimating the Productivity Impacts of Technology Adoption in the Presence of Misclassification," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(1), pages 1-16.
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