Investing In Grain Storage Facilities Under Fluctuating Production
Fluctuating annual harvest volumes create a peak load problem in the provision of grain storage capacity. There are a number of technologies for handling and storing grain, ranging from capital intensive to labour intensive methods. Optimal provision of grain storage capacity can therefore be analysed in the framework of the conventional peak load pricing model. An investment model of grain storage is outlined and the optimal technology choices are determined according to simple investment roles. Capacity of the more capital intensive storage types should be only provided if the extra capital cost is justified by the saving in operating costs, which depends on the expected utilisation of storage. Some level of supply failure is justifiable. An examination of grain storage costs in Western Australia revealed that horizontal storage was the best technology for dealing with most grain storage demand at sites where turnover is limited In the receival period. This concurs with the general investment choices in Western Australia. However, there appears to be a high level of overcapacity at many sites, implying that the cost of supply failure is perceived to be greater than the marketable value of the grain.
Volume (Year): 35 (1991)
Issue (Month): 02 (August)
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Michael A. Crew & Paul R. Kleindorfer, 1976. "Peak Load Pricing with a Diverse Technology," Bell Journal of Economics, The RAND Corporation, vol. 7(1), pages 207-231, Spring.
- Brown, Gardner, Jr & Johnson, M Bruce, 1969. "Public Utility Pricing and Output under Risk," American Economic Review, American Economic Association, vol. 59(1), pages 119-128, March.
- Hall, Nigel H. & Menz, Kenneth M., 1985. "Product Supply Elasticities for the Australian Broadacre Industries, Estimated with a Programming Model," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 53(01), April.
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