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Adoption of Improved Tef Technology Packages in Northern Ethiopia: A Multivariate Probit Approach


Abebaw Assaye
 Endeshaw Habte

Abstract

This study was initiated to understand the adoption level and factors governing the adoption of improved tef technology packages in the northern part of Ethiopia. A multistage sampling procedure was used to select sample households from Amhara and Tigray region in 2018. A multivariate probit (MVP) model involving a system of five equations for the adoption decision of improved tef technologies and practices was estimated using data collected from 484 sample farm households covering ten districts- two from Tigray and eight from Amhara regional states. The result showed that the adoption level of certified tef seed, row planting, recommended weeding frequency, the recommended rate of Urea and recommended rate of DAP/NPS were 40.2%, 35.7%, 69.1%, 65.0%, and 47.5%, respectively. The model results attested that most improved tef production technology packages are complementary; this implies that farm-level policies that affect the use of one improved agricultural technology can have spillover effects on the other technologies. The various demographic, socio-economic, and institutional variables were found to exhibit variable effects on the decision to adopt the different technology components of the improved tef technology package. The unexpected relationship between the frequency of extension contact and application of recommended fertilizer rate requires further investigation which the available data can’t answer. The overall finding of the study underlined the high importance of information related services and institutional support services in the study area to enhance adoption of improved tef technology packages. Therefore, the government should work with development partners and NGOs for the improvement of such services and ease the accessibility and availability of certified seeds and fertilizers as well as the introduction of labor-saving technologies so as to achieve wider adoption of the technologies.


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eISSN: 2415-2382
print ISSN: 0257-2605