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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.
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