000105548 001__ 105548
000105548 005__ 20250206162214.0
000105548 0247_ $$2doi$$a10.22004/ag.econ.105548
000105548 037__ $$a1835-2016-149412
000105548 037__ $$a1835-2016-149792
000105548 041__ $$aeng
000105548 245__ $$aModeling Stochastic Crop Yield Expectations with a Limiting Beta Distribution
000105548 260__ $$c2011-04
000105548 269__ $$a2011-04
000105548 300__ $$a15
000105548 336__ $$aJournal Article
000105548 520__ $$aThe use of plausible stochastic price processes in price risk analysis has allowed advances
not seen in crop yield risk analysis. This study develops a stochastic process for yield
modeling and risk management. The Pólya urn process is an internally consistent dynamic
representation of yield expectations over a growing season that accommodates agronomic
events such as growing degree days. The limiting distribution is the commonly used beta
distribution. Binomial tree analysis of the process allows us to explore hedging decisions
and crop valuation. The method is empirically flexible to accommodate alternative
assumptions on the growing environment, such as intra-season input decisions.
000105548 650__ $$aCrop Production/Industries
000105548 6531_ $$acrop abandonment
000105548 6531_ $$acrop insurance
000105548 6531_ $$aderivative analysis
000105548 6531_ $$agrowing degree days
000105548 6531_ $$aPólya’s urn
000105548 6531_ $$astochastic process
000105548 700__ $$aHennessy, David A.
000105548 773__ $$q177$$o191$$tJournal of Agricultural and Resource Economics$$j36$$k01$$dApril 2011
000105548 8564_ $$9dd262806-f589-4581-aa36-e86cbe94e71b$$s377959$$uhttps://ageconsearch.umn.edu/record/105548/files/JARE_Apr2011__11_pp177-191_Hennessy.pdf
000105548 887__ $$ahttp://purl.umn.edu/105548
000105548 909CO $$ooai:ageconsearch.umn.edu:105548$$pGLOBAL_SET
000105548 912__ $$nSubmitted by Mengyao Luan (luanx012@umn.edu) on 2011-06-01T20:46:07Z
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  Previous issue date: 2011-04
000105548 913__ $$aLicense granted by Mengyao Luan (luanx012@umn.edu) on 2011-06-01T20:42:53Z (GMT):

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000105548 980__ $$a1835
000105548 982__ $$gJournal of Agricultural and Resource Economics>Volume 36, Number 1, April 2011