Farmers’ choice of varieties and demand for improved cassava stems in Nigeria

Authors

  • A Kolapo Department of Agricultural Economics, Obafemi Awolowo University, Ile-Ife, Nigeria
  • OV Ogunyemi Department of Agricultural Economics, Obafemi Awolowo University, Ile-Ife, Nigeria
  • OM Ologundudu Department of Agricultural Extension and Rural Development, University of Ibadan, Ibadan, Nigeria
  • IA Adekunle Department of Agricultural Extension and Rural Development, Obafemi Awolowo University, Ile-Ife, Nigeria
  • MO Akinloye Department of Agricultural Economics, Obafemi Awolowo University, Ile-Ife, Nigeria
  • F Komolehin Department of Agricultural Economics, Obafemi Awolowo University, Ile-Ife, Nigeria

DOI:

https://doi.org/10.3329/ijarit.v11i2.57254

Keywords:

Improved cassava, Varieties demand, Multivariate probit, Nigeria

Abstract

In this study, we used a household level survey to assess choices of varieties and demand for improved cassava varieties. A multivariate probit model was used to examine the determinants of choice decisions of the farmers for different varieties preventing potential endogeneity and measurement error. A Linearized Almost Ideal Demand System (LA/AIDS) model was used to analyze the demand system for improved cassava varieties. The results of the (LA/AIDS) model indicated farmers were very price sensitive to changes in improved stem prices and incomes. We suggest that intervention program that will improve the purchasing power of the farmers should be targeted towards the smallholder cassava farmers to accelerate adoption of improved cassava varieties.

Int. J. Agril. Res. Innov. Tech. 11(2): 42-51, Dec 2021

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Published

2022-01-08

How to Cite

Kolapo, A., Ogunyemi, O., Ologundudu, O., Adekunle, I., Akinloye, M., & Komolehin, F. (2022). Farmers’ choice of varieties and demand for improved cassava stems in Nigeria. International Journal of Agricultural Research, Innovation and Technology, 11(2), 42–51. https://doi.org/10.3329/ijarit.v11i2.57254

Issue

Vol. 11 No. 2 (2021)

Section

Articles

License

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