In this paper, the authors argue that modeling the trend component in real GNP as a random walk is inconsistent with its interpretation as productivity growth. As an alternative, they specify the trend as an ARIMA whose impulse response function follows an S-shaped pattern reflecting the process of diffusion of technical change. Such an ARIMA is employed to build and estimate an UCARIMA using U.S. postwar quarterly data. The authors find that their model, although more parsimonious, fits the data equally as well as the standard random walk plus AR(2) cycle. Moreover, their model has a very low cycle/trend variance ratio.