EFFICIENCY ANALYSIS OF DAIRY FARMS IN THE NORTHERN GREAT PLAIN REGION USING DETERMINISTIC AND STOCHASTIC DEA MODELS

Running any dairy enterprise is a risky activity: the profitability of the enterprise is affected by the price fluctuation of feed and animal health products from inputs, as well as by the fluctuation of end-product prices. Under these circumstances, it is essential for the cattle breeders, in order to survive, to harness the reserves in management as effectively as possible. In this research the efficiency and risk of 32 sample dairy farms were analysed in the Northern Great Plain Region from the Farm Accountancy Data Network (FADN) by applying classical Data Envelopment Analysis (DEA) and stochastic DEA models. The choice of this method is justified by the fact that there was not such an available reliable database by which production functions could have been defined, and DEA makes possible to manage simultaneously some inputs and outputs, i.e. complex decision problems. By using DEA, the sources that cause shortfall on inefficient farms can be identified, analysed and quantified, so corporate decision support can be reinforced successfully. A disadvantage of the classical DEA model is that the stochastic factors of farming cannot be treated either on the side of inputs or outputs; therefore, their results can be adopted with reservations, especially in agricultural models. This may have been because we could not discover that many agricultural applications. Considering the price of inputs and outputs as probability variables, 5000 simulation runs have been done in this research. As a result, it can be stated that at which intervals of the input and output factors can become competitive and the fluctuation of these factors can cause what level of risk at each farm.


Subject(s):
Issue Date:
Apr 04 2013
Publication Type:
Journal Article
PURL Identifier:
http://purl.umn.edu/147425
Published in:
APSTRACT: Applied Studies in Agribusiness and Commerce, Volume 06, Number 5
Page range:
113-122
Total Pages:
10
Series Statement:
6
5




 Record created 2017-04-01, last modified 2017-08-27

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