Trends, Cycles and Convergence

Abstract

This article first discusses ways of decomposing a time series into trend and cyclical components, paying particular attention to a new class of model for cycles. It is shown how using an auxiliary series can help to achieve a more satisfactory decomposition. A discussion of balanced growth then leads on to the construction of new models for converging economies. The preferred models combine unobserved components with an error correction mechanism and allow a decomposition into trend, cycle and convergence components. This provides insight into what has happened in the past, enables the current state of an economy to be more accurately assessed and gives a procedure for the prediction of future observations. The methods are applied to data on the US, Japan and Chile.