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Technology and managerial gaps in adoption of innovation: the case of Ethiopian wheat farmers

Author

Listed:
  • Ashok K. Mishra

    (Arizona State University)

  • Ganesh Thapa

    (Wisconsin Department of Natural Resources, Bureau of Environmental Analysis and Sustainability)

  • Khondoker A. Mottaleb

    (Texas Tech University)

  • Kindie T. Fantaye

    (International Maize and Wheat Improvement Center (CIMMYT))

Abstract

This study investigates technology and managerial gaps between Ethiopian farmers growing local (non-adopters) and improved (adopters) wheat varieties using field survey data. The study uses maximum likelihood estimates of the conventional and sample-selection stochastic production frontier and stochastic metafrontier models (HHL and AOS methods) coupled with statistical matching to assess technology and managerial gaps. The ex-post evaluation reveals that farmers who adopted new technology achieved a minimum of 33% higher yields and 60% higher profits than non-adopters. Technical efficiency is consistently higher among adopters of new, improved varieties than those using local varieties. Significant differences in technology and managerial gaps exist between adopters and non-adopters. Furthermore, the study confirmed that farmers who cultivated improved wheat varieties operate more commercialized agricultural farms than their counterparts. Policymakers could provide incentives to improve access to technology, extension services and farm inputs (such as improved wheat seeds, chemical fertilizers, and irrigation) to enhance the adoption of improved wheat varieties.

Suggested Citation

  • Ashok K. Mishra & Ganesh Thapa & Khondoker A. Mottaleb & Kindie T. Fantaye, 2025. "Technology and managerial gaps in adoption of innovation: the case of Ethiopian wheat farmers," Empirical Economics, Springer, vol. 69(1), pages 1-37, July.
  • Handle: RePEc:spr:empeco:v:69:y:2025:i:1:d:10.1007_s00181-025-02723-2
    DOI: 10.1007/s00181-025-02723-2
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    1. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492, National Bureau of Economic Research, Inc.
    2. Ashok K. Mishra & Saleem Shaik & Aditya R. Khanal & Subir Bairagi, 2018. "Contract farming and technical efficiency: Evidence from low†value and high†value crops in Nepal," Agribusiness, John Wiley & Sons, Ltd., vol. 34(2), pages 426-440, March.
    3. K. M. Mostafizur Rahman & Peter Michael Schmitz & Tobias C. Wronka, 2002. "Comparison of Technical Efficiencies for Rice Production in Bangladesh Under Two Alternative Tenurial Systems," Bangladesh Development Studies, Bangladesh Institute of Development Studies (BIDS), vol. 28(1-2), pages 137-160.
    4. Abdulai, Awudu & Huffman, Wallace, 2000. "Structural Adjustment and Economic Efficiency of Rice Farmers in Northern Ghana," Economic Development and Cultural Change, University of Chicago Press, vol. 48(3), pages 503-520, April.
    5. Cliff Huang & Tai-Hsin Huang & Nan-Hung Liu, 2014. "A new approach to estimating the metafrontier production function based on a stochastic frontier framework," Journal of Productivity Analysis, Springer, vol. 42(3), pages 241-254, December.
    6. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    7. 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.
    8. Diewert, W. E., 1973. "Functional forms for profit and transformation functions," Journal of Economic Theory, Elsevier, vol. 6(3), pages 284-316, June.
    9. Sinyolo, Sikhulumile, 2020. "Technology adoption and household food security among rural households in South Africa: The role of improved maize varieties," Technology in Society, Elsevier, vol. 60(C).
    10. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    11. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    12. Wooldridge, Jeffrey M., 2005. "Violating Ignorability Of Treatment By Controlling For Too Many Factors," Econometric Theory, Cambridge University Press, vol. 21(5), pages 1026-1028, October.
    13. Langyintuo, Augustine S. & Mungoma, Catherine, 2008. "The effect of household wealth on the adoption of improved maize varieties in Zambia," Food Policy, Elsevier, vol. 33(6), pages 550-559, December.
    14. Boris Bravo-Ureta & William Greene & Daniel Solís, 2012. "Technical efficiency analysis correcting for biases from observed and unobserved variables: an application to a natural resource management project," Empirical Economics, Springer, vol. 43(1), pages 55-72, August.
    15. Solis, Daniel & Bravo-Ureta, Boris E. & Quiroga, Ricardo E., 2007. "Soil conservation and technical efficiency among hillside farmers in Central America: a switching regression model," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 51(4), pages 1-20.
    16. Simtowe, Franklin & Amondo, Emily & Marenya, Paswel & Rahut, Dil & Sonder, Kai & Erenstein, Olaf, 2019. "Impacts of drought-tolerant maize varieties on productivity, risk, and resource use: Evidence from Uganda," Land Use Policy, Elsevier, vol. 88(C).
    17. Wanglin Ma & Awudu Abdulai & Renan Goetz, 2018. "Agricultural Cooperatives and Investment in Organic Soil Amendments and Chemical Fertilizer in China," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(2), pages 502-520.
    18. Martin Paul & Kai Mausch & Tesfaye B Woldeyohanes & Thomas Heckelei, 2022. "Three hurdles towards commercialisation: integrating subsistence chickpea producers in the market economy," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(3), pages 668-695.
    19. Silva, João Vasco & Baudron, Frédéric & Reidsma, Pytrik & Giller, Ken E., 2019. "Is labour a major determinant of yield gaps in sub-Saharan Africa? A study of cereal-based production systems in Southern Ethiopia," Agricultural Systems, Elsevier, vol. 174(C), pages 39-51.
    20. Neubauer, Florian & Songsermsawas, Tisorn & Kámiche-Zegarra, Joanna & Bravo-Ureta, Boris E., 2022. "Technical efficiency and technological gaps correcting for selectivity bias: Insights from a value chain project in Nepal," Food Policy, Elsevier, vol. 112(C).
    21. Tadesse Getachew & Mengistu Ketema & Degye Goshu & Degnet Abebaw, 2021. "Technical Efficiency of Wheat Producers in North Shewa Zone of Amhara Region, Central Ethiopia," Sustainable Agriculture Research, Canadian Center of Science and Education, vol. 9(3), pages 1-77, December.
    22. Mesele Belay Zegeye & Abebaw Hailu Fikrie & Anteneh Bizualem Asefa, 2022. "Impact of agricultural technology adoption on wheat productivity: Evidence from North Shewa Zone, Amhara Region, Ethiopia," Cogent Economics & Finance, Taylor & Francis Journals, vol. 10(1), pages 2101223-210, December.
    23. Hailemariam Teklewold & Menale Kassie & Bekele Shiferaw, 2013. "Adoption of Multiple Sustainable Agricultural Practices in Rural Ethiopia," Journal of Agricultural Economics, Wiley Blackwell, vol. 64(3), pages 597-623, September.
    24. Martey, Edward & Etwire, Prince M. & Kuwornu, John K.M., 2020. "Economic impacts of smallholder farmers’ adoption of drought-tolerant maize varieties," Land Use Policy, Elsevier, vol. 94(C).
    25. Vaiknoras, Kate & Larochelle, Catherine, 2021. "The impact of iron-biofortified bean adoption on bean productivity, consumption, purchases and sales," World Development, Elsevier, vol. 139(C).
    26. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    27. Shiferaw, Bekele & Kassie, Menale & Jaleta, Moti & Yirga, Chilot, 2014. "Adoption of improved wheat varieties and impacts on household food security in Ethiopia," Food Policy, Elsevier, vol. 44(C), pages 272-284.
    28. Christine Amsler & Christopher J. O’Donnell & Peter Schmidt, 2017. "Stochastic metafrontiers," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 1007-1020, October.
    29. Kassie, Menale & Shiferaw, Bekele & Muricho, Geoffrey, 2011. "Agricultural Technology, Crop Income, and Poverty Alleviation in Uganda," World Development, Elsevier, vol. 39(10), pages 1784-1795.
    30. Lateef Olalekan Bello & Lloyd J. S. Baiyegunhi & Gideon Danso-Abbeam, 2021. "Productivity impact of improved rice varieties’ adoption: case of smallholder rice farmers in Nigeria," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 30(7), pages 750-766, October.
    31. William Greene, 2010. "A stochastic frontier model with correction for sample selection," Journal of Productivity Analysis, Springer, vol. 34(1), pages 15-24, August.
    32. Timothy J. Coelli & D.S. Prasada Rao & Christopher J. O’Donnell & George E. Battese, 2005. "An Introduction to Efficiency and Productivity Analysis," Springer Books, Springer, edition 0, number 978-0-387-25895-9, January.
    33. Birara Endalew & Mezgebu Aynalem & Adugnaw Anteneh & Habtamu Mossie, 2023. "Sources of wheat production technical inefficiency among smallholder farmers in Northwestern Ethiopia: Beta regression approach," Cogent Economics & Finance, Taylor & Francis Journals, vol. 11(1), pages 2208895-220, December.
    34. Renato Villano & Boris Bravo-Ureta & Daniel Solís & Euan Fleming, 2015. "Modern Rice Technologies and Productivity in the Philippines: Disentangling Technology from Managerial Gaps," Journal of Agricultural Economics, Wiley Blackwell, vol. 66(1), pages 129-154, February.
    35. ASFAW, Milkessa & GETA, Endrias & MITIKU, Fikadu, . "Economic Efficiency Of Smallholder Farmers In Wheat Production: The Case Of Abuna Gindeberet District, Western Ethiopia," Review of Agricultural and Applied Economics (RAAE), Faculty of Economics and Management, Slovak Agricultural University in Nitra, vol. 22(01).
    36. repec:zwi:journl:v:43:y:2012:i:1:p:55-72 is not listed on IDEAS
    37. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    38. Raju Ghimire & Wen-Chi Huang, 2015. "Household wealth and adoption of improved maize varieties in Nepal: a double-hurdle approach," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 7(6), pages 1321-1335, December.
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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy

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