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Technical efficiency of smallholder maize production in Zambia: a stochastic meta-frontier approach

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  • John N. Ng’ombe

Abstract

We determine and compare technical efficiency (TE), technology gap ratios (TGRs) and meta-frontier technical efficiency (MTEs) of maize production between regions using nationally representative panel data collected from 4001 smallholder farm households in Zambia. We estimate the stochastic meta-frontier and region-specific stochastic frontiers based on the ‘true random effects’ framework. Our results show variations in efficiency measures and that smallholder maize production is characterised by increasing returns to scale across all regions, which clearly suggest maize farmers to reduce their average long-term costs by increasing their production scale. We find that some regions are on average more technically efficient than others while those with TE values exceeding 90 per cent operate further below their potential output than those with moderate TE values. Similarly, farm households from regions whose mean TE values are about 90 per cent employ inferior farming techniques to those employed by farmers from regions whose mean TE values are lower. This is in part due to industry-wide specific environmental factors. Most importantly, we find no region to have maize farmers that adopt the most advanced techniques. Results further indicate that all provinces have had either lower or higher TEs, TGRs and MTEs in one period than in another. Generally, our results point to the need to promote superior techniques that would withstand industry-wide specific environmental factors. While it is not possible to find the many reasons for wide variations in TEs, TGRs, and MTEs across regions and time, our results make novel contributions to literature.

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  • John N. Ng’ombe, 2017. "Technical efficiency of smallholder maize production in Zambia: a stochastic meta-frontier approach," Agrekon, Taylor & Francis Journals, vol. 56(4), pages 347-365, October.
  • Handle: RePEc:taf:ragrxx:v:56:y:2017:i:4:p:347-365
    DOI: 10.1080/03031853.2017.1409127
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    1. Ligia Alba Melo-Becerra & Antonio José Orozco-Gallo, 2017. "Technical efficiency for Colombian small crop and livestock farmers: A stochastic metafrontier approach for different production systems," Journal of Productivity Analysis, Springer, vol. 47(1), pages 1-16, February.
    2. Yujiro Hayami, 1969. "Sources of Agricultural Productivity Gap Among Selected Countries," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 51(3), pages 564-575.
    3. Chen-Ming Chen & Tzu-Chun Sheng & Yung-Lieh Yang, 2015. "Market Structure, Government Shareholding and Cost Efficiency in Taiwan's Biotech Industry," Journal of Economics and Management, College of Business, Feng Chia University, Taiwan, vol. 11(1), pages 69-100, January.
    4. Smale, Melinda & Byerlee, Derek & Jayne, Thom, 2011. "Maize revolutions in Sub-Saharan Africa," Policy Research Working Paper Series 5659, The World Bank.
    5. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    6. Federico Belotti & Silvio Daidone & Giuseppe Ilardi & Vincenzo Atella, 2013. "Stochastic frontier analysis using Stata," Stata Journal, StataCorp LP, vol. 13(4), pages 718-758, December.
    7. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Xiao, Xing-Zhi & Lau, Sim-Yee, 2017. "Have regulatory reforms improved the efficiency levels of the Japanese electricity distribution sector? A cost metafrontier-based analysis," Energy Policy, Elsevier, vol. 108(C), pages 606-616.
    8. 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.
    9. Awudu Abdulai & Hendrik Tietje, 2007. "Estimating technical efficiency under unobserved heterogeneity with stochastic frontier models: application to northern German dairy farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 34(3), pages 393-416, September.
    10. Mushunje, A. & Belete, A., 2001. "Efficiency of Zimbabwean Small Scale Communal Farmers," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 40(3), September.
    11. 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.
    12. Mulungu, Kelvin & Tembo, Gelson & Kabwe, Stephen, 2012. "An Economic Analysis of Precision Application of Climate at Reduced Rates," 2012 Eighth AFMA Congress, November 25-29, 2012, Nairobi, Kenya 159407, African Farm Management Association (AFMA).
    13. John N. Ng’ombe & Thomson H. Kalinda & Gelson Tembo, 2017. "Does adoption of conservation farming practices result in increased crop revenue? Evidence from Zambia," Agrekon, Taylor & Francis Journals, vol. 56(2), pages 205-221, April.
    14. Chapoto, Antony & Haggblade, Steven & Hichaambwa, Munguzwe & Kabwe, Stephen & Longabaugh, Steven & Sitko, Nicholas J. & Tschirley, David L., 2012. "Agricultural Transformation in Zambia: Alternative Institutional Models for Accelerating Agricultural Productivity Growth, and Commercialization," Food Security Collaborative Working Papers 132339, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    15. Mkhabela, Thulasizwe S., 2005. "Technical efficiency in a vegetable based mixed-cropping sector in Tugela Ferry, Msinga District, KwaZulu-Natal," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 44(2), pages 1-18, June.
    16. Bao-Guang Chang & Tai-Hsin Huang & Chun-Yi Kuo, 2015. "A comparison of the technical efficiency of accounting firms among the US, China, and Taiwan under the framework of a stochastic metafrontier production function," Journal of Productivity Analysis, Springer, vol. 44(3), pages 337-349, December.
    17. Hayami, Yujiro & Ruttan, Vernon W, 1970. "Agricultural Productivity Differences Among Countries," American Economic Review, American Economic Association, vol. 60(5), pages 895-911, December.
    18. Abdul Nafeo Abdulai & Awudu Abdulai, 2016. "Allocative and scale efficiency among maize farmers in Zambia: a zero efficiency stochastic frontier approach," Applied Economics, Taylor & Francis Journals, vol. 48(55), pages 5364-5378, November.
    19. Alene, AD & Hassan, RM, 2003. "The Determinants Of Farm-Level Technical Efficiency Among Adopters Of Improved Maize Production Technology In Western Ethiopia," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 42(1).
    20. 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.
    21. Vernon W. Ruttan, 1971. "Technology and the Environment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 53(5), pages 707-717.
    22. Haggblade, Steven & Tembo, Gelson, 2003. "Conservation farming in Zambia:," EPTD discussion papers 108, International Food Policy Research Institute (IFPRI).
    23. Kwesiga, Freddie & Franzel, Steven & Mafongoya, Paramu & Ajayi, Olu & Phiri, Donald & Katanga, Roza & Kuntashula, Elias & Place, Frank & Chirwa, Teddy, 2005. "Improved fallows in Eastern Zambia: history, farmer practice and impacts," EPTD discussion papers 130, International Food Policy Research Institute (IFPRI).
    24. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    25. George E. Battese & D. S. Prasada Rao, 2002. "Technology Gap, Efficiency, and a Stochastic Metafrontier Function," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(2), pages 87-93, August.
    26. Ngoma, Hambulo & Mason, Nicole M. & Sitko, Nicholas, 2015. "Does Minimum Tillage with Planting Basins or Ripping Raise Maize Yields? Meso-panel Data Evidence from Zambia," Food Security Collaborative Working Papers 198701, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    27. Ng'ombe, John & Kalinda, Thomson, 2015. "A Stochastic Frontier Analysis of Technical Efficiency of Maize Production Under Minimum Tillage in Zambia," Sustainable Agriculture Research, Canadian Center of Science and Education, vol. 4(2).
    28. Baltagi, Badi H & Griffin, James M, 1988. "A General Index of Technical Change," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 20-41, February.
    29. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    30. Huang, Tai-Hsin & Chiang, Dien-Lin & Tsai, Chao-Min, 2015. "Applying the New Metafrontier Directional Distance Function to Compare Banking Efficiencies in Central and Eastern European Countries," Economic Modelling, Elsevier, vol. 44(C), pages 188-199.
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    2. Caleb I. Adewale & Elias Munezero & Elly K. Ndyomugyenyi & Basil Mugonola, 2024. "Determinants of technical efficiency of pig production systems in northern Uganda: a Stochastic Frontier approach," SN Business & Economics, Springer, vol. 4(8), pages 1-21, August.

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