In this paper, the authors use polynomial adjustment cost (PAC) models to analyze and forecast the main components of the U.S. trade sector. For instance, they model and measure the elasticities of imports and exports to changes in the exchange rate and income. PAC models provide a theoretical justification for the presence of lags within a dynamic equation where optimizing agents' expectations are completely rational and forward looking. This approach thereby adds theoretical depth to a model that has a good forecasting performance. To the authors' knowledge, this paper is the first study to model the U.S. trade sector using a PAC approach. Overall, the models' main elasticities are reasonable. Moreover, the authors find that the out-ofsample forecasting performance of their PAC models is at least as good as that of other models. Their results show that this theoretical structure is not added at the expense of the empirical features of the models.