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A Geometric Analysis of Technological Heterogeneity in the Agricultural Sector: Evidence from Maize in Tanzania

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  • Nchare, Karim
  • Vitouley, Marcel
  • Kaila, Heidi
  • Liu, Yanyan

Abstract

This paper presents a new framework to measure farm-level heterogeneity, and productivity change, and to study the rate and direction of technical change within an agricultural sector. Building on the seminal works of Hildenbrand (1981) and Dosi et al. (2016), we show how, while relaxing most of the standard assumptions from production theory, discrete geometry is an effective tool for productivity analysis and technical change in agricultural economics. We apply the framework to a rich panel data from maize farmers in Tanzania to investigate the dynamics of technical heterogeneity and agricultural productivity growth.

Suggested Citation

  • Nchare, Karim & Vitouley, Marcel & Kaila, Heidi & Liu, Yanyan, 2022. "A Geometric Analysis of Technological Heterogeneity in the Agricultural Sector: Evidence from Maize in Tanzania," PRCI Research Papers 330119, Michigan State University, Department of Agricultural, Food and Resource Economics, Food Security Group.
    • Handle: RePEc:ags:miprrp:330119
    DOI: 10.22004/ag.econ.330119
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    References listed on IDEAS

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    1. 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.
    2. Giovanni Dosi & Marco Grazzi & Luigi Marengo & Simona Settepanella, 2016. "Production Theory: Accounting for Firm Heterogeneity and Technical Change," Journal of Industrial Economics, Wiley Blackwell, vol. 64(4), pages 875-907, December.
    3. Léopold Simar & Valentin Zelenyuk, 2011. "Stochastic FDH/DEA estimators for frontier analysis," Journal of Productivity Analysis, Springer, vol. 36(1), pages 1-20, August.
    4. 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.
    5. Giller, K.E. & Tittonell, P. & Rufino, M.C. & van Wijk, M.T. & Zingore, S. & Mapfumo, P. & Adjei-Nsiah, S. & Herrero, M. & Chikowo, R. & Corbeels, M. & Rowe, E.C. & Baijukya, F. & Mwijage, A. & Smith,, 2011. "Communicating complexity: Integrated assessment of trade-offs concerning soil fertility management within African farming systems to support innovation and development," Agricultural Systems, Elsevier, vol. 104(2), pages 191-203, February.
    6. Tjalling C. Koopmans, 1977. "Examples of Production Relations Based on Microdata," International Economic Association Series, in: G. C. Harcourt (ed.), The Microeconomic Foundations of Macroeconomics, chapter 5, pages 144-178, Palgrave Macmillan.
    7. Hildenbrand, Werner, 1981. "Short-Run Production Functions Based on Microdata," Econometrica, Econometric Society, vol. 49(5), pages 1095-1125, September.
    8. van Dijk, Michiel & Morley, Tom & Jongeneel, Roel & van Ittersum, Martin & Reidsma, Pytrik & Ruben, Ruerd, 2017. "Disentangling agronomic and economic yield gaps: An integrated framework and application," Agricultural Systems, Elsevier, vol. 154(C), pages 90-99.
    9. 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.
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