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Title: Identifying risk-efficient strategies using stochastic frontier analysis and simulation: An application to irrigated cropping in Australia
Contributor(s): Power, Brendan (author); Cacho, Oscar J (author)orcid 
Publication Date: 2014
DOI: 10.1016/j.agsy.2013.11.002
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Abstract: In irrigated cropping, as with any other industry, profit and risk are inter-dependent. An increase in profit would normally coincide with an increase in risk, and this means that risk can be traded for profit. It is desirable to manage a farm so that it achieves the maximum possible profit for the desired level of risk. This paper identifies risk-efficient cropping strategies that allocate land and water between crop enterprises for a case study of an irrigated farm in Southern Queensland, Australia. This is achieved by applying stochastic frontier analysis to the output of a simulation experiment. The simulation experiment involved changes to the levels of business risk by systematically varying the crop sowing rules in a bioeconomic model of the case study farm. This model utilises the multi-field capability of the process based Agricultural Production System Simulator (APSIM) and is parameterised using data collected from interviews with a collaborating farmer. We found sowing rules that increased the farm area sown to cotton caused the greatest increase in risk-efficiency. Increasing maize area also improved risk-efficiency but to a lesser extent than cotton. Sowing rules that increased the areas sown to wheat reduced the risk-efficiency of the farm business. Sowing rules were identified that had the potential to improve the expected farm profit by ca. $50,000 Annually, without significantly increasing risk. The concept of the shadow price of risk is discussed and an expression is derived from the estimated frontier equation that quantifies the trade-off between profit and risk.
Publication Type: Journal Article
Source of Publication: Agricultural Systems, v.125, p. 23-32
Publisher: Elsevier BV
Place of Publication: The Netherlands
ISSN: 0308-521X
Field of Research (FOR): 070107 Farming Systems Research
140201 Agricultural Economics
070103 Agricultural Production Systems Simulation
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
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