Two different types of tests for the cointegrating rank of VAR processes with a deterministic shift in the level have been proposed in the literature. The first proposal is based on the LR principle using a specific Gaussian model set-up. In the second proposal the time series are adjusted for...

Two different types of tests for the cointegrating rank of VAR processes with a deterministic shift in the level have been proposed in the literature. The first proposal is based on the LR principle using a specific Gaussian model set-up. In the second proposal the time series are adjusted for...

This paper develops test procedures for testing the validity of general linear identifying restrictions imposed on cointegrating vectors in the context of a vector autoregressive model. In addition to overidentifying restrictions the considered restrictions may also involve normalizing...

In applied time series analysis, checking for autocorrelation in a fitted model is a routine diagnostic tool. Therefore it is useful to know the asymptotic and small sample properties of the standard tests for the case when some of the variables are cointegrated. The properties of residual...

A central assumption for identifying structural shocks in vector autoregressive (VAR) models via heteroskedasticity is the time-invariance of the impact effects of the shocks. It is shown how that assumption can be tested when longrun restrictions are available for identifying structural shocks....

In structural vector autoregressive (SVAR) models identifying restrictions for shocks and impulse responses are usually derived from economic theory or institutional constraints. Sometimes the restrictions are insufficient for identifying all shocks and impulse responses. In this paper it is...

A small system of German economic variables consisting of the money stock M3, Gross National Product (GNP) and a bond rate is used to illustrate the power of cointegration analysis and the usefulness of some recently developed tools for this kind of analysis. Testing for the cointegrating rank...

Vector autoregressive moving-average (VARMA) processes are suitable models for producing linear forecasts of sets of time series variables. They provide parsimonious representations of linear data generation processes. The setup for these processes in the presence of stationary and cointegrated...

A central assumption for identifying structural shocks in vector autoregressive (VAR) models via heteroskedasticity is the time-invariance of the impact effects of the shocks. It is shown how that assumption can be tested when longrun restrictions are available for identifying structural shocks....