Abstract

As the world’s population grows and the potential to increase production by bringing more resources into use becomes more limited, it is natural that the efficiency with which farmers use available resources would become more important as a topic of investigation. Therefore, this study aimed at analyzing the economic efficiency of barley production in Chole district using cross sectional data collected from 150 randomly selected sample households during 2012/13 production season. Cobb-Douglas production function was fitted using stochastic production frontier approach to estimate technical, allocative and economic efficiency levels, whereas Tobit model was used to identify factors affecting efficiency levels of the sample farmer. The results indicated that there was a significant inefficiency in barley production in the study area. Accordingly, the mean technical, allocative and economic efficiencies of barley producer farmers were 78.20, 46.05 and 35.26 percent, respectively. This implies that output can be increased by 21.8 percent or cost can be reduced by 53.95 percent given the existing level of technology and resources. This inefficiency however, can be improved if factors that determine efficiency level of farmers in the production of barley in the study area are identified and targeted. Results of the Tobit model revealed that age, education, total cultivated land, extension contact, family size, soil fertility, off/non-farm income, sex, crop rotation and livestock ownership positively and significantly affected technical efficiency while land fragmentation and total expenditure had negative and significant effect. Result of the Tobit model also revealed that age, education, total cultivated land, training, crop rotation and livestock ownership positively and significantly affected allocative efficiency while extension contact, land fragmentation, distance of the farm from homestead, and total expenditure were found to have negative and significant effect. Among the factors hypothesized to affect the level of economic efficiency, age, education, training, family size, off/non-farm income, crop rotation and livestock ownership were found to have positive and significant effect on economic efficiency in barley production. The results of the study indicated that there was a room to increase the efficiency of barley producers in the study area through policies and strategies directed towards the above mentioned determinants. Keywords : Cobb-Douglas, stochastic frontier, Tobit. DOI: 10.7176/JRDM/66-03 Publication date: June 30th 2020

Highlights

  • Ethiopia, the country with an area of about 1.12 million square kilometers, is one of the most populous Counties in Africa with the population of 73.75 million in 2007 with annual growth rate of 2.6% (CSA, 2008)

  • Description of the Study Area Chole district is located in Oromia National Regional State of East Arsi Zone at about 219 km away from Addis Ababa

  • In the descriptive part, simple measures of central tendencies and variations, frequency and percentages were used; and in the econometric analyses, a stochastic frontier approach was used to estimate the level of barley production efficiencies and a Tobit model to identify factors that affect the efficiency level of the farmers

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Summary

Introduction

The country with an area of about 1.12 million square kilometers, is one of the most populous Counties in Africa with the population of 73.75 million in 2007 with annual growth rate of 2.6% (CSA, 2008). This study tries to analyze the economic efficiency of barley production, and its determinants in one of the districts of East Arsi zone, known for the production of this crop, Chole. Objectives of the Study The general objective of the study was to assess economic efficiency of barley producers in Chole district of East Arsi zone. Methodology Description of the Study Area Chole district is located in Oromia National Regional State of East Arsi Zone at about 219 km away from Addis Ababa. It is located at 60 22’ and 8014’N latitude and 40o 02’and 40o19ʹE longitude.

Sampling Techniques
Efficiency measurement
Subject to
TEi i'
Estimates of Production and Cost Functions
Return to scale
Efficiency scores
Findings
Determinants of efficiency differential among farmers
Full Text
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