When Point Estimates Miss the Point: Stochastic Modeling of WTO Restrictions

Abstract

Point estimates of agricultural and trade policy impacts often paint an incomplete or even misleading picture. For many purposes it is important to estimate a distribution of outcomes. Stochastic modeling can be especially important when policies have asymmetric effects or when there is interest in the tails of distributions. Both of these factors are important in evaluating World Trade Organization (WTO) commitments on internal support measures. Point estimates based on a continuation of 2005 U.S. agricultural policies and average values for external factors indicate that U.S. support would remain well below agreed commitments under the Uruguay Round Agreement on Agriculture (URAA). Stochastic estimates indicate that the mean value of the U.S. Aggregate Measure of Support (AMS) is substantially greater than the deterministic point estimate. In 41.8 percent of 500 stochastic outcomes, the URAA AMS limit is exceeded at least once between 2006 and 2014.