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Agricultural Technical Efficiency of Smallholder Farmers in Ethiopia: A Stochastic Frontier Approach

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  • Markose Chekol Zewdie

    (Department of Engineering Management, Faculty of Business and Economics, University of Antwerp, Stadscampus, Prinsstraat 13, 2000 Antwerp, Belgium
    Department of Economics, Peda Campus, College of Business and Economics, Bahir Dar University, Bahir Dar P.O. Box 79, Ethiopia)

  • Michele Moretti

    (Department of Engineering Management, Faculty of Business and Economics, University of Antwerp, Stadscampus, Prinsstraat 13, 2000 Antwerp, Belgium
    Department of Agriculture, Food and Environment, University of Pisa, via del Borghetto 80, 56124 Pisa, Italy)

  • Daregot Berihun Tenessa

    (Department of Economics, Peda Campus, College of Business and Economics, Bahir Dar University, Bahir Dar P.O. Box 79, Ethiopia)

  • Zemen Ayalew Ayele

    (Department of Agricultural Economics, Zenzelima Campus, Bahir Dar University, Bahir Dar P.O. Box 79, Ethiopia)

  • Jan Nyssen

    (Department of Geography, Ghent University, Krijgslaan 281, S8, 9000 Gent, Belgium)

  • Enyew Adgo Tsegaye

    (Department of Natural Resource Management, Zenzelima Campus, Bahir Dar University, Bahir Dar P.O. Box 79, Ethiopia)

  • Amare Sewnet Minale

    (Department of Geography and Environmental Studies, Peda Campus, Bahir Dar University, Bahir Dar P.O. Box 79, Ethiopia)

  • Steven Van Passel

    (Department of Engineering Management, Faculty of Business and Economics, University of Antwerp, Stadscampus, Prinsstraat 13, 2000 Antwerp, Belgium
    Department of Economics, Peda Campus, College of Business and Economics, Bahir Dar University, Bahir Dar P.O. Box 79, Ethiopia)

Abstract

In the past decade, to improve crop production and productivity, Ethiopia has embarked on an ambitious irrigation farming expansion program and has introduced new large- and small-scale irrigation initiatives. However, in Ethiopia, poverty remains a challenge, and crop productivity per unit area of land is very low. Literature on the technical efficiency (TE) of large-scale and small-scale irrigation user farmers as compared to the non-user farmers in Ethiopia is also limited. Investigating smallholder farmers’ TE level and its principal determinants is very important to increase crop production and productivity and to improve smallholder farmers’ livelihood and food security. Using 1026 household-level cross-section data, this study adopts a technology flexible stochastic frontier approach to examine agricultural TE of large-scale irrigation users, small-scale irrigation users and non-user farmers in Ethiopia. The results indicate that, due to poor extension services and old-style agronomic practices, the mean TE of farmers is very low (44.33%), implying that there is a wider room for increasing crop production in the study areas through increasing the TE of smallholder farmers without additional investment in novel agricultural technologies. Results also show that large-scale irrigation user farmers (21.05%) are less technically efficient than small-scale irrigation user farmers (60.29%). However, improving irrigation infrastructure shifts the frontier up and has a positive impact on smallholder farmers’ output.

Suggested Citation

  • Markose Chekol Zewdie & Michele Moretti & Daregot Berihun Tenessa & Zemen Ayalew Ayele & Jan Nyssen & Enyew Adgo Tsegaye & Amare Sewnet Minale & Steven Van Passel, 2021. "Agricultural Technical Efficiency of Smallholder Farmers in Ethiopia: A Stochastic Frontier Approach," Land, MDPI, vol. 10(3), pages 1-17, March.
  • Handle: RePEc:gam:jlands:v:10:y:2021:i:3:p:246-:d:508182
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    References listed on IDEAS

    as
    1. Subal C. Kumbhakar & Hung-Jen Wang, 2015. "Estimation of Technical Inefficiency in Production Frontier Models Using Cross-Sectional Data," Springer Books, in: Subhash C. Ray & Subal C. Kumbhakar & Pami Dua (ed.), Benchmarking for Performance Evaluation, edition 127, chapter 0, pages 1-73, Springer.
    2. Anbes Tenaye, 2020. "Technical Efficiency of Smallholder Agriculture in Developing Countries: The Case of Ethiopia," Economies, MDPI, vol. 8(2), pages 1-27, April.
    3. Abdul-Rahaman, Awal & Abdulai, Awudu, 2018. "Do farmer groups impact on farm yield and efficiency of smallholder farmers? Evidence from rice farmers in northern Ghana," Food Policy, Elsevier, vol. 81(C), pages 95-105.
    4. Thomas P. Triebs & David S. Saal & Pablo Arocena & Subal C. Kumbhakar, 2016. "Estimating economies of scale and scope with flexible technology," Journal of Productivity Analysis, Springer, vol. 45(2), pages 173-186, April.
    5. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    6. Varela-Ortega, Consuelo & M. Sumpsi, Jose & Garrido, Alberto & Blanco, Maria & Iglesias, Eva, 1998. "Water pricing policies, public decision making and farmers' response: implications for water policy," Agricultural Economics, Blackwell, vol. 19(1-2), pages 193-202, September.
    7. Nelson Mango & Clifton Makate & Lulseged Tamene & Powell Mponela & Gift Ndengu, 2018. "Adoption of Small-Scale Irrigation Farming as a Climate-Smart Agriculture Practice and Its Influence on Household Income in the Chinyanja Triangle, Southern Africa," Land, MDPI, vol. 7(2), pages 1-19, April.
    8. E.T. Seyoum & G.E. Battese & E.M. Fleming, 1998. "Technical efficiency and productivity of maize producers in eastern Ethiopia: a study of farmers within and outside the Sasakawa‐Global 2000 project," Agricultural Economics, International Association of Agricultural Economists, vol. 19(3), pages 341-348, December.
    9. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    10. Tafesse W. Gezahegn & Steven Van Passel & Tekeste Berhanu & Marijke D’haese & Miet Maertens, 2020. "Do bottom-up and independent agricultural cooperatives really perform better? Insights from a technical efficiency analysis in Ethiopia," Agrekon, Taylor & Francis Journals, vol. 59(1), pages 93-109, January.
    11. Gebrehiwot, Kidanemariam G. & Makina, Daniel & Woldu, Thomas, 2017. "The impact of micro-irrigation on households’ welfare in the northern part of Ethiopia: an endogenous switching regression approach," Studies in Agricultural Economics, Research Institute for Agricultural Economics, vol. 119(3), December.
    12. Coelli, Tim & Fleming, Euan, 2004. "Diversification economies and specialisation efficiencies in a mixed food and coffee smallholder farming system in Papua New Guinea," Agricultural Economics, Blackwell, vol. 31(2-3), pages 229-239, December.
    13. Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107029514, October.
    14. Hadri, Kaddour, 1999. "Estimation of a Doubly Heteroscedastic Stochastic Frontier Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 359-363, July.
    15. Kees Jan Van Garderen & Chandra Shah, 2002. "Exact interpretation of dummy variables in semilogarithmic equations," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 149-159, June.
    16. Bravo-Ureta, Boris E. & Higgins, Daniel & Arslan, Aslihan, 2020. "Irrigation infrastructure and farm productivity in the Philippines: A stochastic Meta-Frontier analysis," World Development, Elsevier, vol. 135(C).
    17. 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.
    18. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-111, January.
    19. H.E.T. Holgersson & L. Nordstr�m & Ö. Öner, 2014. "Dummy variables vs. category-wise models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(2), pages 233-241, February.
    20. Hung-Jen Wang, 2002. "Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 18(3), pages 241-253, November.
    21. Akridge, Jay T. & Hertel, Thomas W., 1992. "Cooperative and Investor-Oriented Firm Efficiency: A Multiproduct Analysis," Journal of Agricultural Cooperation, National Council of Farmer Cooperatives, vol. 7, pages 1-14.
    22. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
    23. Jules Ngango & Seung Gyu Kim, 2019. "Assessment of Technical Efficiency and Its Potential Determinants among Small-Scale Coffee Farmers in Rwanda," Agriculture, MDPI, vol. 9(7), pages 1-12, July.
    24. Zewdie, Markose Chekol & Van Passel, Steven & Cools, Jan & Tenessa, Daregot Berihun & Ayele, Zemen Ayalew & Tsegaye, Enyew Adgo & Minale, Amare Sewnet & Nyssen, Jan, 2019. "Direct and indirect effect of irrigation water availability on crop revenue in northwest Ethiopia: A structural equation model," Agricultural Water Management, Elsevier, vol. 220(C), pages 27-35.
    25. Abdulai Adams & Bedru Balana & Nicole Lefore, 2020. "Efficiency of Small-scale Irrigation Farmers in Northern Ghana: A Data Envelopment Analysis Approach," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 14(3), pages 332-352, August.
    26. Fitsum Assefa Adela & Joachim Aurbacher & Gumataw Kifle Abebe, 2019. "Small-scale irrigation scheme governance - poverty nexus: evidence from Ethiopia," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 11(4), pages 897-913, August.
    27. Andre Croppenstedt & Mulat Demeke, 1997. "An empirical study of cereal crop production and technical efficiency of private farmers in Ethiopia: a mixed fixed-random coefficients approach," Applied Economics, Taylor & Francis Journals, vol. 29(9), pages 1217-1226.
    28. Dorosh, Paul A. & Rashid, Shahidur, 2013. "Food and agriculture in Ethiopia: Progress and policy challenges," Issue briefs 74, International Food Policy Research Institute (IFPRI).
    29. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    30. Seyoum, E. T. & Battese, G. E. & Fleming, E. M., 1998. "Technical efficiency and productivity of maize producers in eastern Ethiopia: a study of farmers within and outside the Sasakawa-Global 2000 project," Agricultural Economics, Blackwell, vol. 19(3), pages 341-348, December.
    31. Zewdie, Markose Chekol & Van Passel, Steven & Moretti, Michele & Annys, Sofie & Tenessa, Daregot Berihun & Ayele, Zemen Ayalew & Tsegaye, Enyew Adgo & Cools, Jan & Minale, Amare Sewnet & Nyssen, Jan, 2020. "Pathways how irrigation water affects crop revenue of smallholder farmers in northwest Ethiopia: A mixed approach," Agricultural Water Management, Elsevier, vol. 233(C).
    32. 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.
    33. Jan Schepers, 2016. "On regression modelling with dummy variables versus separate regressions per group: Comment on Holgersson et al," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(4), pages 674-681, March.
    34. Hamed Taherdoost, 2016. "Sampling Methods in Research Methodology; How to Choose a Sampling Technique for Research," Post-Print hal-02546796, HAL.
    35. Ngango, Jules & Lee, Jungmyung & Kim, Seung Gyu, 2019. "Determinants of technical efficiency among small-scale coffee farmers in Rwanda," 2019 Annual Meeting, July 21-23, Atlanta, Georgia 291139, Agricultural and Applied Economics Association.
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