Heteroskedasticity In Crop Yield Models
This study examines three alternative models of correcting for heteroskedasticity in wheat yield: the time trend variance, the GARCH, and an econometric model that includes the potential sources of heteroskedasticity. Nonnested test results suggest that modeling the sources of heteroskedasticity is the preferred procedure. Including potential sources of heteroskedasticity as explanatory variables removed the heteroskedasticity in the sample wheat yields. The results also suggest that the GARCH specification is a promising model of correcting for heteroskedasticity when the sources cannot be identified. The time trend variance model alone may misspecify the true variance structure.
Volume (Year): 17 (1992)
Issue (Month): 01 (July)
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- Satheesh V. Aradhyula & Matthew T. Holt, 1988.
"GARCH Time Series Models: An Application to Retail Livestock Prices,"
Food and Agricultural Policy Research Institute (FAPRI) Publications
88-wp29, Food and Agricultural Policy Research Institute (FAPRI) at Iowa State University.
- Aradhyula, Satheesh V. & Holt, Matthew T., 1988. "Garch Time-Series Models: An Application To Retail Livestock Prices," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 13(02), December.
- Satheesh V. Aradhyula & Matthew T. Holt, 1988. "GARCH Time Series Models: An Application to Retail Livestock Prices," Center for Agricultural and Rural Development (CARD) Publications 88-wp29, Center for Agricultural and Rural Development (CARD) at Iowa State University.
- A. J. Singh & D. Byerlee, 1990. "Relative Variability In Wheat Yields Across Countries And Over Time," Journal of Agricultural Economics, Wiley Blackwell, vol. 41(1), pages 21-32.
- Just, Richard E. & Pope, Rulon D., 1978. "Stochastic specification of production functions and economic implications," Journal of Econometrics, Elsevier, vol. 7(1), pages 67-86, February.
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