Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/240244 
Erscheinungsjahr: 
2019
Quellenangabe: 
[Journal:] Agricultural and Food Economics [ISSN:] 2193-7532 [Volume:] 7 [Issue:] 1 [Publisher:] Springer [Place:] Heidelberg [Year:] 2019 [Pages:] 1-15
Verlag: 
Springer, Heidelberg
Zusammenfassung: 
This study employs stochastic frontier analysis (SFA) correcting for sample selection bias, to determine technical efficiency (TE) and technology gap using cross-sectional data collected from 543 rice farmers in Northern Ghana. The results showed that corrected sample selection TE estimates were marginally higher. Without the appropriate corrections, inefficiency is overestimated, while the gap in performance between irrigation farmers and their rainfed counterparts is underestimated. We recommend that authorities in Ghana should work with development partners, especially in the implementation of small village-dam projects, and also to expand the existing irrigation schemes. Bunds should also be constructed around rice production valleys across northern Ghana so that farmers could expand their farm sizes to increase production. It is important also that the government's input subsidy programme be structured to cater for experienced and younger farmers who consider agriculture as a business.
Schlagwörter: 
Rice production
Sample selection
Stochastic frontier
Technical efficiency
Northern Ghana
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