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Cost-reflective pricing: empirical insights into irrigators’ preferences for water tariffs

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Listed:
  • Cooper, Bethany
  • Crase, Lin
  • Rose, John M.

Abstract

Using prices to improve the efficiency with which water resources are allocated is now widely accepted in principle if somewhat difficult to achieve in practice. Whilst there are some technical difficulties associated with full-cost recovery in irrigation, the lack of political will to tackle reform remains a significant impediment. This article reports the results of an empirical investigation into farmers’ preferences for changes to water prices and tariff structures. We conclude that some of the preferences of farmers are conducive to price reform. We also find evidence that public subsidy of infrastructure in irrigation is not always aligned with the preferences of farmers.

Suggested Citation

  • Cooper, Bethany & Crase, Lin & Rose, John M., 2018. "Cost-reflective pricing: empirical insights into irrigators’ preferences for water tariffs," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(2), April.
  • Handle: RePEc:ags:aareaj:313573
    DOI: 10.22004/ag.econ.313573
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    References listed on IDEAS

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    1. Alec Zuo & Céline Nauges & Sarah Ann Wheeler, 2015. "Farmers' exposure to risk and their temporary water trading," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 42(1), pages 1-24.
    2. Hugh Sibly & Richard Tooth, 2014. "The consequences of using increasing block tariffs to price urban water," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(2), pages 223-243, April.
    3. Flynn, Terry N. & Louviere, Jordan J. & Peters, Tim J. & Coast, Joanna, 2007. "Best-worst scaling: What it can do for health care research and how to do it," Journal of Health Economics, Elsevier, vol. 26(1), pages 171-189, January.
    4. Terry Flynn, 2010. "Using Conjoint Analysis and Choice Experiments to Estimate QALY Values," PharmacoEconomics, Springer, vol. 28(9), pages 711-722, September.
    5. Lin Crase & Nicholas Pawsey & Sue O'Keefe, 2013. "A Note on Contradictions in Australian Water Policy," Economic Papers, The Economic Society of Australia, vol. 32(3), pages 353-359, September.
    6. Pat Auger & Timothy Devinney & Jordan Louviere, 2007. "Using Best–Worst Scaling Methodology to Investigate Consumer Ethical Beliefs Across Countries," Journal of Business Ethics, Springer, vol. 70(3), pages 299-326, February.
    7. K. William Easter & Yang Liu, 2005. "Cost Recovery and Water Pricing for Irrigation and Drainage Projects," World Bank Publications - Reports 37385, The World Bank Group.
    8. Office of Health Economics, 2007. "The Economics of Health Care," For School 001490, Office of Health Economics.
    9. Wheeler, Sarah Ann & Zuo, Alec & Bjornlund, Henning, 2014. "Investigating the delayed on-farm consequences of selling water entitlements in the Murray-Darling Basin," Agricultural Water Management, Elsevier, vol. 145(C), pages 72-82.
    10. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D. With contributions by-Name:Adamowicz,Wiktor, 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304, Enero.
    11. Louviere, Jordan & Lings, Ian & Islam, Towhidul & Gudergan, Siegfried & Flynn, Terry, 2013. "An introduction to the application of (case 1) best–worst scaling in marketing research," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 292-303.
    12. Nicholas Pawsey & Lin Crase, 2013. "The Mystique of Water Pricing and Accounting," Economic Papers, The Economic Society of Australia, vol. 32(3), pages 328-339, September.
    13. Lin Crase & Sue O’Keefe & Brian Dollery, 2011. "Some Observations about the Reactionary Rhetoric Circumscribing the Guide to the Murray–Darling Basin Plan," Economic Papers, The Economic Society of Australia, vol. 30(2), pages 195-207, June.
    14. Dan Rigby & Francisco Alcon & Michael Burton, 2010. "Supply uncertainty and the economic value of irrigation water," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 37(1), pages 97-117, March.
    15. Lin Crase & Sue O'Keefe & Brian Dollery, 2008. "Urban Water Pricing: Practical Perspectives And Customer Preferences," Economic Papers, The Economic Society of Australia, vol. 27(2), pages 194-206, June.
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