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G. Tranter (2019)
Australia and New ZealandAllies against the Rising Sun
David Adamson, Thilak Mallawaarachchi, J. Quiggin (2007)
Water Use and Salinity in the Murray-Darling Basin: A State-Contingent ModelAgricultural & Natural Resource Economics
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Optimisation of Production Under Uncertainty
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R. Chambers, J. Quiggin (2007)
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Farm Management and Climate: Catalogue no: 4625.0. Australian Bureau of Statistics
J. Quiggin, R. Chambers (2006)
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Roger Jones, Celeste Young, J. Handmer (2013)
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Optimisation of Production Under Uncertainty: The State-Contingent Approach
Nolan Miller, Alexander Wagner, R. Zeckhauser (2012)
Solomonic separation: Risk decisions as productivity indicatorsJournal of Risk and Uncertainty, 46
Céline Nauges, C. O'Donnell, J. Quiggin (2013)
Risk and Uncertainty Program TITLE : Uncertainty and Technical Efficiency in Finnish Agriculture : A State-contingent Approach
(2008)
Farm Management and Climate: Catalogue no: 4625.0
David Adamson, Thilak Mallawaarachchi, J. Quiggin (2009)
Declining Inflows and More Frequent Droughts in the Murray–Darling Basin: Climate Change, Impacts and AdaptationWater Sustainability eJournal
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Estimating State‐Contingent Production FrontiersWiley-Blackwell: American Journal of Agricultural Economics
Roger Jones, Celeste Young, J. Handmer, A. Keating, G. Mekala, P. Sheehan (2013)
Valuing Adaptation Under Rapid Change: Research Summary for Policy Makers
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Uncertainty, production, choice, and agency - The state-contingent approach.
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Insurance milk
J. Crean, K. Parton, J. Mullen, Randall Jones (2013)
Representing Climatic Uncertainty in Agricultural Models – An Application of State‐Contingent TheoryWiley-Blackwell: Australian Journal of Agricultural & Resource Economics
J. Chavas (2008)
A Cost Approach to Economic Analysis Under State‐Contingent Production UncertaintyERN: Agricultural Economics (Topic)
The agricultural sector is commonly regarded as one of the most vulnerable to climate change. Current understanding of the impact of climate change on this sector relies on the underlying assumptions about farmers’ possible responses to weather variability, including changes in crop choice, input combinations and land management practices. Many previous analyses rely on the implicit (and restrictive) assumption that farmers operate under a fixed technology set across different states of nature. This assumption, represented through stochastic production or profit functions, is commonly made but seldom tested and may understate farmers’ responses to climate change if state‐contingent production technologies are, in reality, more flexible. The potential for farmers to adapt production technologies in response to unforeseen events is at the core of the state‐contingent approach. Advanced in Chambers and Quiggin (2000), the theory contends that producers can manage uncertainty through the allocation of productive inputs to different states of nature. In this article, we test the assumption that farmers’ observed behaviour is consistent with the state‐contingent production theory using farm‐level data from Australia. More precisely, we estimate the milk production technology for a sample of irrigated dairy farms from the southern Murray–Darling Basin over the period from 2006–2007 to 2009–2010.
The Australian Journal of Agricultural Resource Economics – Wiley
Published: Jan 1, 2017
Keywords: ; ; ;
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