Issues and Strategies for Aggregate Supply Response Estimation for Policy Analyses
We demonstrate the use of the small-sample econometrics principles and strategies to come up with reliable yield and acreage models for policy analyses. We focus on demonstrating the importance of proper representation of systematic and random components of the model for improving forecasting precision along with more reliable confidence intervals for the forecasts. A probability distribution function modeling approach, which has been shown to provide more reliable confidence intervals for the dependent variable forecasts than the standard models that assume error term normality, is used to estimate cotton supply response in the Southeastern United States.
Volume (Year): 36 (2004)
Issue (Month): 02 (August)
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- Hal Hill & Budy P. Resosudarmo, 2012. "Introduction," Bulletin of Indonesian Economic Studies, Taylor & Francis Journals, vol. 48(2), pages 129-142, August.
- Octavio A. Ramirez & Sukant Misra & James Field, 2003. "Crop-Yield Distributions Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 108-120.
- Ramirez, Octavio A. & Somarriba, Eduardo, 2000. "Risk And Returns Of Diversified Cropping Systems Under Nonnormal, Cross-, And Autocorrelated Commodity Price Structures," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 25(02), December.
- Ramirez, Octavio A. & Fadiga, Mohamadou L., 2003. "Forecasting Agricultural Commodity Prices with Asymmetric-Error GARCH Models," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 28(01), April.
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