Government policy impacts on the U.S. wheat sector

Abstract

A representative subset of previous econometric studies of demand, supply and market price determination for U.S. wheat and other selected crops was reviewed and assessed from the perspective of endogenizing farm program policy linkages. The greatest limitation identified with these previous sector modeling efforts was their restrictiveness in modeling only those policy instruments in force when they were constructed. With the Food Security Act of 198S as a background, this study considered a broad set of current and potential policy instruments in an effort to promote proactive policy impact analysis. The wheat sector simulation model developed herein reflects the behavioral assumptions that wheat producers maximize expected returns above variable costs per acre subject to institutional and technological constraints, and that consumers maximize expected utility subject to a budget constraint. Since the model's objective is to make long-term projections as opposed to short-term forecasts, structural specifications of the policy transmission mechanisms were chosen over time series specifications which often exclude these mechanisms. The wheat sector model developed in this study is designed to be incorporated into the COMGEM macroeconomic model, a large-scale econometric model of the U. S. economy containing some 600 non-linear simultaneous equations. Owing primarily to empirical and theoretical considerations regarding the selection of estimators, the equations reported in this study were estimated using the OLS estimator. The estimated coefficients associated with the explanatory variables were largely statistically significant. The performance of the resulting empirical model was evaluated based upon standard goodness-of-fit criteria as well as the conformity of the coefficients with a priori expected signs. Once the model was estimated, it was solved using the Gauss-Seidel solution procedure. The model was simulated both within and beyond the sample period to further assess the model's predictive ability. This model was then used to investigate the potential impacts of a 15 percent annual increase in the target price for wheat, and the institution of a marketing loan program for wheat.