Estimation of Technical Efficiency of Open Shed Broiler Farmers in Punjab, Pakistan: A Stochastic Frontier Analysis

Salamat Ali, Shahid Ali, Bakhtawar Riaz


This study was conducted to estimate the level of technical efficiency of open shed broiler farmers in Punjab, Pakistan. Data was randomly collected from 60 broiler farmers using multistage sampling technique during January-February, 2014. Stochastic frontier Cobb-Douglas production function was used for analysis of data. Maximum likelihood estimation technique was employed for estimation. The analysis revealed that the mean technical efficiency of open shed broiler farmers was 0.880 ranging from 0.440 to 0.985.  This means that if the average broiler farmer in the sample was to achieve the technical efficiency level of its most efficient counterpart than the average farmer could realize 10.50 per cent cost savings. In other words, with the same available resources and technology, an average broiler farmer could increase broiler production by 10.50 per cent. Similarly the most technically inefficient broiler farmer could reveal cost savings of 54.50 per cent. Results further showed that number of day old chicks, feed and labor positively and significantly affected broiler production while the effect of vaccination was negative and that of capacity of shed was positive but statistically insignificant. Results of technical inefficiency effect model revealed that with the increase in age, education and membership with association, technical efficiency of broiler farmers increased. Based upon these findings it is suggested that government and extension workers should educate open shed broiler farmers to use high quality day old chicks and feed for highest possible output and cost savings. Education programs for awareness among broiler farmers to use vaccinated day old chicks and quality resources for enhancing broiler production in the country is also a good policy option.

Keywords:Open Shed Broiler Farmers, Technical Efficiency, Stochastic Frontier, Cobb-Douglas Production Function, MLE, Punjab, Pakistan

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