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Valuing seasonal climate forecasts in a state-contingent manner

Author

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  • Jason Crean
  • Kevin Parton
  • John Mullen
  • Peter Hayman

Abstract

type="main" xml:id="ajar12041-abs-0001"> We applied state-contingent theory to climate uncertainty at a farm level to assess the value of seasonal climate forecasts in the Central West region of NSW. We find that modelling uncertainty in a state-contingent manner results in a lower estimate of forecast value than the typical expected value approach. We attribute this finding to a more conservative long-term farm plan in the discrete stochastic programming (DSP) model, which is better balanced for climate uncertainty. Hence, a climate forecast, even though it still revises probabilities held by farmers, does not call forth such large changes in farm plans and associated farm incomes. We then use the DSP model to assess how attributes of a hypothetical forecasting system, particularly its skill and timeliness, as well as attributes of the decision environment, influence its value. Lastly, we assess the value of current operational forecast systems and show that the value derived from seasonal climate forecasts is relatively limited in the case study region largely because of low skill embodied in forecasts at the time when major farm decisions are being made.

Suggested Citation

  • Jason Crean & Kevin Parton & John Mullen & Peter Hayman, 2015. "Valuing seasonal climate forecasts in a state-contingent manner," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 59(1), pages 61-77, January.
  • Handle: RePEc:bla:ajarec:v:59:y:2015:i:1:p:61-77
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    File URL: http://hdl.handle.net/10.1111/ajar.2015.59.issue-1
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    Citations

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    Cited by:

    1. Steele C. West & Amin W. Mugera & Ross S. Kingwell, 2024. "The impact of repayment obligations arising as a by‐product of input use on partial inefficiency: Evidence from Western Australian farm businesses," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 68(3), pages 678-700, July.
    2. Darbyshire, Rebecca & Crean, Jason & Cashen, Michael & Anwar, Muhuddin Rajin & Broadfoot, Kim M & Simpson, Marja & Cobon, David H & Pudmenzky, Christa & Kouadio, Louis & Kodur, Shreevatsa, 2020. "Insights into the value of seasonal climate forecasts to agriculture," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(04), January.
    3. Rebecca Darbyshire & Jason Crean & Michael Cashen & Muhuddin Rajin Anwar & Kim M Broadfoot & Marja Simpson & David H Cobon & Christa Pudmenzky & Louis Kouadio & Shreevatsa Kodur, 2020. "Insights into the value of seasonal climate forecasts to agriculture," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(4), pages 1034-1058, October.
    4. Loch, Adam & Auricht , Christopher & Adamson, David & Mateo, Luis, 2020. "Markets, mis-direction and motives: A factual analysis of hoarding and speculation in southern Murray–Darling Basin water markets," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(02), January.
    5. Adam Loch & Christopher Auricht & David Adamson & Luis Mateo, 2021. "Markets, mis‐direction and motives: A factual analysis of hoarding and speculation in southern Murray–Darling Basin water markets," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(2), pages 291-317, April.
    6. Mitter, Hermine & Schmid, Erwin, 2019. "Computing the economic value of climate information for water stress management exemplified by crop production in Austria," Agricultural Water Management, Elsevier, vol. 221(C), pages 430-448.

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