Issues and Strategies for Aggregate Supply Response Estimation for Policy Analyses

Octavio A. Ramirez, Samarendu Mohanty (), Carlos E. Carpio and Megan Denning

Journal of Agricultural & Applied Economics, 2004, vol. 36, issue 2, pages 351-367

Abstract: 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.

Keywords: nonnormality; probability distribution function; supply response (search for similar items in EconPapers)
JEL-codes: Q11 Q18 C32 (search for similar items in EconPapers)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Access Statistics for this article

Journal of Agricultural & Applied Economics is edited by Jeffrey M. Gillespie

More articles in Journal of Agricultural & Applied Economics from Southern Agricultural Economics Association
Address: Secretary/Treasurer, Dept. of Agricultural and Applied Economics, University of Georgia, Georgia Experiment Station, Griffin, Georgia 30223
Series data maintained by Chung L. Huang ().