A Case Study in Prediction: The Market for Watermelons
This paper discusses two forecasting experiments involving models of the watermelon market. The first experiment compares the forecasts of an interdependent model estimated by limited information, single equation with those of a model using least squares reduced form. The second experiment compares the forecasts of the interdependent model with those of a causal chain model. It is found that the forecasts of the interdependent model are generally better than those of the alternative models.