LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

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

Photo from wikipedia

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… Click to show full abstract

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.

Keywords: frontier analysis; rice; stochastic frontier; northern ghana; sample selection

Journal Title: Agricultural and Food Economics
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.