000174315 001__ 174315
000174315 005__ 20170827201406.0
000174315 037__ $$a329-2016-13214
000174315 041__ $$aen_US
000174315 084__ $$aG12
000174315 084__ $$aH2
000174315 084__ $$aQ18.
000174315 245__ $$aTail Dependence is to be Expected Among Crop Yields
000174315 246__ $$aTail Dependence of Crop Yield
000174315 260__ $$c2014
000174315 269__ $$a2014
000174315 270__ $$pHennessy,   David
000174315 336__ $$aConference Paper/ Presentation
000174315 520__ $$aRate setting methods for crop yield and revenue contracts employ methods that presume that correlations are state invariant. Whether this is true matters. If yield-yield correlations strengthen when crops are subject to widespread stress then diversification opportunities for private insurers weaken when most needed. For the government’s book of business, such tail dependence will increase the transactions and political costs of inter-agency reallocation of funds. In this paper we propose a simple model of yields according to interactions between the weather outcome and land limitations as in the United States Soil Conservation Service’s land capability classification. Our model shows that yield-yield tail dependence is to be expected and, furthermore, should take a particular form. Yield correlations should be stronger in the left and right tails than in the center, i.e., U shaped state-conditional correlation is hypothesized. Using Risk Management Agency unit level data and a variety of statistics, we find strong evidence in favor of the U shaped tail dependence hypothesis. But the goodness-of-fit test fails to reject the standard Gaussian Copula model, which can be due to power of the tests, sampling error, and/or relatively weak tail dependence over the sample years. We conclude that existing RMA rate-setting methods are deficient.
000174315 542__ $$fLicense granted by Xiaodong Du (xdu23@wisc.edu) on 2014-06-30T14:23:41Z (GMT):

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000174315 650__ $$aCrop Production/Industries
000174315 650__ $$aRisk and Uncertainty
000174315 6531_ $$aactuarial fairness
000174315 6531_ $$acrop insurance
000174315 6531_ $$aGaussian copula
000174315 6531_ $$areinsurance
000174315 6531_ $$asystemic risk
000174315 700__ $$aDu, Xiaodong
000174315 700__ $$aHennessy, David
000174315 700__ $$aFeng, Hongli
000174315 773__ $$d2014
000174315 8564_ $$s904009$$uhttp://ageconsearch.umn.edu/record/174315/files/AAEA%202014%20Tail_Dependence_Du_Hennessy_Feng.pdf
000174315 887__ $$ahttp://purl.umn.edu/174315
000174315 909CO $$ooai:ageconsearch.umn.edu:174315$$qGLOBAL_SET
000174315 912__ $$nSubmitted by Xiaodong Du (xdu23@wisc.edu) on 2014-06-30T14:26:18Z
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  Previous issue date: 2014
000174315 982__ $$gAgricultural and Applied Economics Association>2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota
000174315 980__ $$a329