Measuring productivity of production factors in broiler breeding industry using fuzzy regression

To calculate partial and total productivity of production factors in broiler farms in Yazd province, 72 manufacturing units were selected based on simple random sampling method and their information and statistics were collected for one production period in the second half of 2013. To measure productivity, the Cobb-Douglas production function was estimated using classic and fuzzy regression methods. Workforce and energy had significant positive effects on broiler meat production. Feed had the highest coefficient (0.71 in the classic regression and 0.58 in fuzzy regression) and was the most effective production factor. Partial productivity of all variables and total production factors were also calculated. Productivity of total production factors was 1.90 in classic regression; concerning fuzzy regression with confidence interval of 90%, upper and lower bounds were 2.86 and 1.37 respectively.

Measuring productivity of production factors in broiler breeding industry using fuzzy regression Keywords:

productivity , production function , broiler , Fuzzy Regression