Artikel

Correcting for sample selection in stochastic frontier analysis: Insights from rice farmers in Northern Ghana

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.

Sprache
Englisch

Erschienen in
Journal: Agricultural and Food Economics ; ISSN: 2193-7532 ; Volume: 7 ; Year: 2019 ; Issue: 1 ; Pages: 1-15 ; Heidelberg: Springer

Klassifikation
Wirtschaft
Thema
Rice production
Sample selection
Stochastic frontier
Technical efficiency
Northern Ghana

Ereignis
Geistige Schöpfung
(wer)
Azumah, Shaibu Baanni
Donkoh, Samuel Arkoh
Awuni, Joseph Agebase
Ereignis
Veröffentlichung
(wer)
Springer
(wo)
Heidelberg
(wann)
2019

DOI
doi:10.1186/s40100-019-0130-z
Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Azumah, Shaibu Baanni
  • Donkoh, Samuel Arkoh
  • Awuni, Joseph Agebase
  • Springer

Entstanden

  • 2019

Ähnliche Objekte (12)