It is common to transform data to stationarity, such as by differencing and demeaning, before estimating factor models in macroeconomics. Imposing these transformations, however, limit opportunities to learn about trending behaviour. Trends and deterministic processes can play a central role in...

Factor models can cope with many variables without running into scarce degrees of freedom problems often faced in a regression-based analysis. In this article we review recent work on dynamic factor models that have become popular in macroeconomic policy analysis and forecasting. By means of an...

This paper attempts to find the possibilities of simplifying a multiple time series. We consider a dynamic factor model, Zt=i=1minfiXt-i+Gt, where Zt is a k-dimensional Gaussian stationary time series, Xt is an unobservable r-dimensional factor series (Kr) and t is a (K-r)-dimensional white...

A survey is provided dealing with the formulation of modelling problems for dynamic factor models, and the various algorithm possibilities for solving these modelling problems. Emphasis is placed on understanding requirements for the handling of errors, noting the relevance of the proposed...