Abstract

<p>This study analyzes the level and determinants of technical efficiency of soybean farms in the Saboba and Chereponi districts of northern Ghana. A multi-stage sampling technique was used to select 200 soybean farmers from which cross-sectional data was collected using a structured questionnaire. Data collected includes farmers’ socio-economic characteristics such as age and education as well as input and output quantities and prices. Data was analyzed using the stochastic frontier approach. Results showed a mean technical efficiency estimate of 53 percent and the return to scale was 0.75. Location of farm, participation in the Agricultural Value Chain Mentorship Project and age of farmer were found to be important in explaining technical inefficiency among soybean farmers. This implies that farmers in the short run can increase their production by 47 percent by adopting practices of the best soybean farms in Saboba and Chereponi districts of northern Ghana.</p>

Highlights

  • Soybean (Glycine max L.) is an important legume in Ghana

  • The second and third hypotheses are rejected inefficiency effects are present in the model and are not non-stochastic which implies that the use of the traditional ordinary least square (OLS) regression technique cannot be supported by the data

  • A 1 percent increase in land kept under soybean production will result in an increase in production of about 0.85 percent ceteris paribus

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Summary

Introduction

Soybean (Glycine max L.) is an important legume in Ghana. The crop is a good source of plant protein and is used in the preparation of food and feed. Ghana’s Council for Scientific and Industrial Research, CSIR, through the AVCMP and other development projects have been extending soybean technologies to farmers in northern Ghana including those in the Saboba and Chereponi districts. These technologies include good land preparation practices, use of certified seed, dibbling, Integrated Soil Fertility Management (ISFM), Integrated Pest Management (IPM), timely execution of farm operations, soybean-rice rotation among others. In spite of these interventions, MoFA (2011) reported that farmer’s average soybean yields (1.5 Mt/Ha) were well below achievable yields (2.3 Mt/Ha).

Theoretical Framework
Stochastic Frontiers
Statement of Hypothesis
Sampling and Data Collection Method
Empirical Results
Estimates of the Frontier Model
Inefficiency Model
Technical Efficiency
Conclusions
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