Valuing Catastrophic Losses for Perennial Agricultural Crops
Courts are often required to estimate changes in welfare to agricultural operations from catastrophic events. For example, courts must assign damages in lawsuits, such as with pesticide drift cases, or determine 'just compensation' when the government takes private land for public use, as...
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Published in | IDEAS Working Paper Series from RePEc |
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Main Authors | , , , |
Format | Paper |
Language | English |
Published |
St. Louis
Federal Reserve Bank of St. Louis
01.01.2003
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Online Access | Get full text |
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Summary: | Courts are often required to estimate changes in welfare to agricultural operations from catastrophic events. For example, courts must assign damages in lawsuits, such as with pesticide drift cases, or determine 'just compensation' when the government takes private land for public use, as with the removal of dairy farms from environmentally sensitive land or destruction of canker-contaminated citrus trees. In economics, the traditional method of estimating changes in producer welfare is the computation of lost producer surplus, but courts rarely use this method. Instead, they turn to substitute valuation methods that may not fully capture welfare change, such as changes in land value, tree replacement value, and total revenue. This study examines various measures for valuing the back-to-back catastrophic freezes that occurred in the Florida citrus industry in the 1980s. We first use the traditional method to determine the welfare change due to a freeze (1) for a citrus grove that loses one crop and is able to return to full production the next year (simulating destruction of annual crops), and (2)the lower measure of welfare loss due to a citrus grove that loses all of its trees and is abandoned or is replanted. The lower measure is used to simulate the legal doctrine of avoidable consequences. These measures are then compared to substitute valuation measures that have been used by courts to determine welfare changes. For case 1, total revenue overestimated losses by 35.6%. For case 2, total revenue overestimates losses by 55.3%, tree replacement value underestimates losses by 93.6%, and changes in land value underestimates losses by 13.2%. |
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