The rank of the spectral density matrix conveys relevant information in a variety of statistical modelling scenarios. This note shows how to estimate the rank of the spectral density matrix at any given frequency. The method presented is valid for any hermitian positive de?nite matrix estimate...

The rank of the spectral density matrix conveys relevant information in a variety of modelling scenarios. Phillips (1986) showed that a necessary condition for cointegration is that the spectral density matrix of the innovation sequence at frequency zero is of a reduced rank. In a recent paper...

Standard measures of prices are often contaminated by transitory shocks. This has prompted economists to suggest the use of measures of underlying in?ation to formulate monetary policy and assist in forecasting observed in?ation. Recent work has concentrated on modelling large datasets using...

In this paper we use a Dynamic Factor model to retrieve vulnerability indicators able to predict financial turmoil. A stochastic simulation experiment is then used to produce the corresponding probability forecasts regarding the currency crisis events a®ecting a number of East Asian countries...

In a factor-augmented regression, the forecast of a variable depends on a few factors estimated from a large number of predictors. But how does one determine the appropriate number of factors relevant for such a regression? Existing work has focused on criteria that can consistently estimate the...

Several ways of modelling non-linear state space models have been suggested. The extended Kalman Filter is a tractable way of doing so. One application is to consumer durable demand. Models explaining this flow are normally conditioned on the stock. For the UK, measures of the stock are...