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Issues and Strategies for Aggregate Supply Response Estimation for Policy Analyses

Published online by Cambridge University Press:  28 April 2015

Octavio A. Ramirez ,
Samarendu Mohanty ,
Carlos E. Carpio  and
Megan Denning
Octavio A. Ramirez
Affiliation:
New Mexico State University, Las Cruces, NM
Samarendu Mohanty
Affiliation:
Texas Tech University, Lubbock, TX
Carlos E. Carpio
Affiliation:
North Carolina State University, Raleigh, NC
Megan Denning
Affiliation:
Texas Tech University
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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

nonnormalityprobability distribution functionsupply responseQ11Q18C32
Type
Invited Paper Sessions
Information
Journal of Agricultural and Applied Economics , Volume 36 , Issue 2 , August 2004 , pp. 351 - 367
Copyright
Copyright © Southern Agricultural Economics Association 2004

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