Diffusion of Technical Change and the Decomposition of Output into Trend and Cycle

Abstract

In this paper we argue that modelling the trend component in real GNP as a random walk is inconsistent with its interpretation as productivity growth. As an alternative, we 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 USA postwar quarterly data. We find that our model, although more parsimonious, fits the data equally well than the standard random walk plus AR(2) cycle. Moreover, our model has a very low cycle/trend variance ratio.