We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
Online ordering will be unavailable from 17:00 GMT on Friday, April 25 until 17:00 GMT on Sunday, April 27 due to maintenance. We apologise for the inconvenience.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure [email protected]
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Given an equipment complement, a specific crop mix has a probability distribution for whole-farm net returns. Increasing crop acreage while holding the set of equipment constant will reduce fixed costs per acre, but it will also increase the length of time required to complete crucial field operations such as planting and harvesting. Thus, the probability of encountering weather-related delays in fieldwork will increase. This increase in delays may cause a decline in yields and changes in the distribution of net returns. This paper develops a Target MOTAD model capable of capturing intra-year impacts on profit that arise from the timing of planting and harvesting operations as well as inter-year impacts on profits that are due to variations in economic and weather-related factors. The model relies on estimates of available fieldwork time and a crop's harvestable yield in different time periods throughout the harvest season.
Hurricanes have caused substantial damage in parts of the U.S. Damages are increasing, perhaps as part of a natural cycle or perhaps in part related to global warming. This paper examines the economic damages that hurricanes cause to U.S. agriculture, estimates the increased damage from an increase in hurricane frequency/intensity, and examines the way that sectoral reactions reduce damages. The simulation results show that hurricanes and associated adjustments cause widespread damage and redistribute agricultural welfare. We find that crop mix shifts of vulnerable crops from stricken to nonstricken regions significantly mitigate hurricane damages.
Recommend this
Email your librarian or administrator to recommend adding this to your organisation's collection.