How Are Crop Yields Distributed?
Six popular crop yield distributions are compared to determine which best describes yield fluctuations out-of-sample. For 183 crop and county combinations, each distribution is estimated and ranked according to its log-likelihood function observed at out-of-sample observations. A semiparametric model dominates the contest for most crops and counties, likely due to its flexibility and treatment of heteroskedasticity. Most other models ranked lower because their variance equation performed poorly out-of-sample.
|Date of creation:||2002|
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- Terry L. Kastens & Gary W. Brester, 1996. "Model Selection and Forecasting Ability of Theory-Constrained Food Demand Systems," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(2), pages 301-312.
- Barry K. Goodwin & Alan P. Ker, 1998. "Nonparametric Estimation of Crop Yield Distributions: Implications for Rating Group-Risk Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 139-153.
- Weninger, Quinn & Just, Richard E., 1999.
"Are Crop Yields Normally Distributed?,"
Staff General Research Papers
5064, Iowa State University, Department of Economics.
- Norwood, F. Bailey & Ferrier, Peyton Michael & Lusk, Jayson L., 2001. "Model Selection Criteria Using Likelihood Functions And Out-Of-Sample Performance," 2001 Conference, April 23-24, 2001, St. Louis, Missouri 18947, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
- Norwood, F. Bailey & Schroeder, Ted C., 2000. "Usefulness Of Placement-Weight Data In Forecasting Fed Cattle Marketings And Prices," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 32(01), April.
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