Improved Construction of diffusion indexes for macroeconomic forecasting

Abstract

This article proposes a modified method for the construction of diffusionindexes in macroeconomic forecasting using principal component regres-sion. The method aims to maximize the amount of variance of the origi-nal predictor variables retained by the diffusion indexes, by matching thedata windows used for constructing the principal components and for es-timating the diffusion index models. The method is applied to constructforecasts of eight monthly US macroeconomic time series, using the dataset of Stock and Watson (2002a). The results show that the proposedmethod leads, on average, to simpler models with smaller forecast errorsthan previously used methods.principal components;forecasting;factor construction