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...

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...

Long-run restrictions have been used extensively for identifying structural shocks in vector autoregressive (VAR) analysis. Such restrictions are typically justidentifying but can be checked by utilizing changes in volatility. This paper reviews and contrasts the volatility models that have been...

We use a cointegrated structural vector autoregressive model to investigate the relation between euro area monetary policy and the stock market. Since there may be an instantaneous causal relation we consider long-run identifying restrictions for the structural shocks and also use (conditional)...