Assessing technical efficiency of Moghani sheep flocks of Ardebil province: Application of data envelopment analysis method

Document Type : Research Paper

Authors

1 Ph.D Student, Department of Animal Sciences, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran

2 Professor, Department of Animal Sciences, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran

3 Associate Professor, Department of Animal Sciences, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran

4 Assistant Professor, Department of Agricultural Economics, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran

Abstract

As the resources are limited, improving efficiency of sheep farming is of high importance in Iran. In the present study, the technical efficiency of Moghani sheep flocks was investigated using the method of data envelopment analysis, considering constant (CRS) or variable (VRS) returns to scale. Data of year 2015 on inputs for the amount of concentrate, forage and labor as well as outputs including the amount of meat, milk, wool and fertilizer were collected from 214 Moghani sheep flocks through interviews and questionnaires. Data analysis was performed using Deap 2.1 software. The average technical efficiencies with CRS and VRS were 0.978 and 0.977, respectively, showing high efficiency in studied flocks. With CRS and VRS, there were 14 and 25 flocks being technically efficient, respectively, and could be introduced as reference flocks to inefficient ones. The results showed that with VRS, some reduction in flock size, labor, forage, concentrate, rangelands roughages and health costs as 2.99, 2.99, 2.63, 2.79, 2.73 and 6.41 percent, respectively, would let inefficient flocks to become efficient, while maintaining the same level of previous production. The estimates of return to scale showed that most of Moghani sheep flocks had an increasing return to scale, and are able to benefit from scale-based savings and lowered cost per output unit.

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References

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Animal Production Research
Volume 7, Issue 1
June 2018
Pages 31-40

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